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[GH-ISSUE #1508] Error: llama runner process has terminated on M2 #817

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opened 2026-04-12 10:29:37 -05:00 by GiteaMirror · 5 comments
GiteaMirror commented 2026-04-12 10:29:37 -05:00
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Originally created by @milioe on GitHub (Dec 13, 2023).
Original GitHub issue: https://github.com/ollama/ollama/issues/1508

I'm currently running Ollama on a MacBook Air m2 (8GB)

I firstly installed Ollama through brew install ollama and got Error: llama runner process has terminated after pulling and running mistral:instruct and mistral:latest .

After that, I uninstalled using brew uninstall ollama then installing it through website. I ran the following commands:

  • ollama pull mistral:instruct
  • ollama run mistral

and I got the same error:
Error: llama runner process has terminated

I checked the logs using cat ~/.ollama/logs/server.log and I got this:

2023/12/13 13:01:18 llama.go:434: starting llama runner
2023/12/13 13:01:18 llama.go:492: waiting for llama runner to start responding
{"timestamp":1702494078,"level":"INFO","function":"main","line":2656,"message":"build info","build":417,"commit":"23b5e12"}
{"timestamp":1702494078,"level":"INFO","function":"main","line":2663,"message":"system info","n_threads":4,"n_threads_batch":-1,"total_threads":8,"system_info":"AVX = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | "}
llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from /Users/emiliosandoval/.ollama/models/blobs/sha256:c70fa74a8e81c3bd041cc2c30152fe6e251fdc915a3792147147a5c06bc4b309 (version GGUF V3 (latest))
llama_model_loader: - tensor    0:                token_embd.weight q4_0     [  4096, 32000,     1,     1 ]
llama_model_loader: - tensor    1:              blk.0.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor    2:              blk.0.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor    3:              blk.0.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor    4:         blk.0.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor    5:            blk.0.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor    6:              blk.0.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor    7:            blk.0.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor    8:           blk.0.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor    9:            blk.0.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   10:              blk.1.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   11:              blk.1.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   12:              blk.1.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   13:         blk.1.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   14:            blk.1.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   15:              blk.1.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   16:            blk.1.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   17:           blk.1.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   18:            blk.1.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   19:              blk.2.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   20:              blk.2.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   21:              blk.2.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   22:         blk.2.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   23:            blk.2.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   24:              blk.2.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   25:            blk.2.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   26:           blk.2.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   27:            blk.2.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   28:              blk.3.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   29:              blk.3.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   30:              blk.3.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   31:         blk.3.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   32:            blk.3.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   33:              blk.3.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   34:            blk.3.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   35:           blk.3.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   36:            blk.3.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   37:              blk.4.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   38:              blk.4.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   39:              blk.4.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   40:         blk.4.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   41:            blk.4.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   42:              blk.4.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   43:            blk.4.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   44:           blk.4.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   45:            blk.4.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   46:              blk.5.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   47:              blk.5.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   48:              blk.5.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   49:         blk.5.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   50:            blk.5.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   51:              blk.5.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   52:            blk.5.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   53:           blk.5.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   54:            blk.5.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   55:              blk.6.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   56:              blk.6.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   57:              blk.6.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   58:         blk.6.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   59:            blk.6.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   60:              blk.6.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   61:            blk.6.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   62:           blk.6.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   63:            blk.6.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   64:              blk.7.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   65:              blk.7.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   66:              blk.7.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   67:         blk.7.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   68:            blk.7.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   69:              blk.7.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   70:            blk.7.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   71:           blk.7.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   72:            blk.7.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   73:              blk.8.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   74:              blk.8.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   75:              blk.8.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   76:         blk.8.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   77:            blk.8.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   78:              blk.8.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   79:            blk.8.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   80:           blk.8.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   81:            blk.8.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   82:              blk.9.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   83:              blk.9.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   84:              blk.9.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   85:         blk.9.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   86:            blk.9.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   87:              blk.9.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   88:            blk.9.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   89:           blk.9.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   90:            blk.9.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   91:             blk.10.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   92:             blk.10.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   93:             blk.10.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor   94:        blk.10.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor   95:           blk.10.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   96:             blk.10.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor   97:           blk.10.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor   98:          blk.10.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor   99:           blk.10.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  100:             blk.11.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  101:             blk.11.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  102:             blk.11.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  103:        blk.11.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  104:           blk.11.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  105:             blk.11.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  106:           blk.11.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  107:          blk.11.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  108:           blk.11.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  109:             blk.12.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  110:             blk.12.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  111:             blk.12.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  112:        blk.12.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  113:           blk.12.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  114:             blk.12.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  115:           blk.12.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  116:          blk.12.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  117:           blk.12.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  118:             blk.13.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  119:             blk.13.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  120:             blk.13.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  121:        blk.13.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  122:           blk.13.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  123:             blk.13.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  124:           blk.13.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  125:          blk.13.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  126:           blk.13.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  127:             blk.14.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  128:             blk.14.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  129:             blk.14.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  130:        blk.14.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  131:           blk.14.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  132:             blk.14.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  133:           blk.14.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  134:          blk.14.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  135:           blk.14.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  136:             blk.15.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  137:             blk.15.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  138:             blk.15.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  139:        blk.15.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  140:           blk.15.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  141:             blk.15.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  142:           blk.15.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  143:          blk.15.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  144:           blk.15.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  145:             blk.16.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  146:             blk.16.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  147:             blk.16.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  148:        blk.16.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  149:           blk.16.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  150:             blk.16.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  151:           blk.16.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  152:          blk.16.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  153:           blk.16.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  154:             blk.17.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  155:             blk.17.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  156:             blk.17.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  157:        blk.17.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  158:           blk.17.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  159:             blk.17.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  160:           blk.17.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  161:          blk.17.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  162:           blk.17.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  163:             blk.18.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  164:             blk.18.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  165:             blk.18.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  166:        blk.18.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  167:           blk.18.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  168:             blk.18.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  169:           blk.18.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  170:          blk.18.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  171:           blk.18.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  172:             blk.19.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  173:             blk.19.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  174:             blk.19.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  175:        blk.19.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  176:           blk.19.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  177:             blk.19.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  178:           blk.19.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  179:          blk.19.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  180:           blk.19.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  181:             blk.20.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  182:             blk.20.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  183:             blk.20.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  184:        blk.20.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  185:           blk.20.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  186:             blk.20.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  187:           blk.20.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  188:          blk.20.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  189:           blk.20.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  190:             blk.21.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  191:             blk.21.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  192:             blk.21.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  193:        blk.21.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  194:           blk.21.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  195:             blk.21.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  196:           blk.21.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  197:          blk.21.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  198:           blk.21.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  199:             blk.22.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  200:             blk.22.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  201:             blk.22.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  202:        blk.22.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  203:           blk.22.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  204:             blk.22.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  205:           blk.22.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  206:          blk.22.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  207:           blk.22.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  208:             blk.23.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  209:             blk.23.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  210:             blk.23.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  211:        blk.23.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  212:           blk.23.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  213:             blk.23.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  214:           blk.23.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  215:          blk.23.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  216:           blk.23.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  217:             blk.24.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  218:             blk.24.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  219:             blk.24.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  220:        blk.24.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  221:           blk.24.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  222:             blk.24.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  223:           blk.24.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  224:          blk.24.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  225:           blk.24.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  226:             blk.25.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  227:             blk.25.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  228:             blk.25.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  229:        blk.25.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  230:           blk.25.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  231:             blk.25.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  232:           blk.25.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  233:          blk.25.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  234:           blk.25.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  235:             blk.26.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  236:             blk.26.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  237:             blk.26.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  238:        blk.26.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  239:           blk.26.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  240:             blk.26.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  241:           blk.26.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  242:          blk.26.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  243:           blk.26.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  244:             blk.27.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  245:             blk.27.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  246:             blk.27.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  247:        blk.27.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  248:           blk.27.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  249:             blk.27.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  250:           blk.27.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  251:          blk.27.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  252:           blk.27.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  253:             blk.28.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  254:             blk.28.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  255:             blk.28.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  256:        blk.28.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  257:           blk.28.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  258:             blk.28.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  259:           blk.28.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  260:          blk.28.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  261:           blk.28.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  262:             blk.29.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  263:             blk.29.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  264:             blk.29.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  265:        blk.29.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  266:           blk.29.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  267:             blk.29.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  268:           blk.29.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  269:          blk.29.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  270:           blk.29.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  271:             blk.30.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  272:             blk.30.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  273:             blk.30.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  274:        blk.30.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  275:           blk.30.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  276:             blk.30.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  277:           blk.30.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  278:          blk.30.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  279:           blk.30.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  280:             blk.31.attn_q.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  281:             blk.31.attn_k.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  282:             blk.31.attn_v.weight q4_0     [  4096,  1024,     1,     1 ]
llama_model_loader: - tensor  283:        blk.31.attn_output.weight q4_0     [  4096,  4096,     1,     1 ]
llama_model_loader: - tensor  284:           blk.31.ffn_gate.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  285:             blk.31.ffn_up.weight q4_0     [  4096, 14336,     1,     1 ]
llama_model_loader: - tensor  286:           blk.31.ffn_down.weight q4_0     [ 14336,  4096,     1,     1 ]
llama_model_loader: - tensor  287:          blk.31.attn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  288:           blk.31.ffn_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  289:               output_norm.weight f32      [  4096,     1,     1,     1 ]
llama_model_loader: - tensor  290:                    output.weight q6_K     [  4096, 32000,     1,     1 ]
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.name str              = mistralai
llama_model_loader: - kv   2:                       llama.context_length u32              = 32768
llama_model_loader: - kv   3:                     llama.embedding_length u32              = 4096
llama_model_loader: - kv   4:                          llama.block_count u32              = 32
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
llama_model_loader: - kv   6:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv   7:                 llama.attention.head_count u32              = 32
llama_model_loader: - kv   8:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                       llama.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  11:                          general.file_type u32              = 2
llama_model_loader: - kv  12:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr[str,32000]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  19:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  20:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  21:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   65 tensors
llama_model_loader: - type q4_0:  225 tensors
llama_model_loader: - type q6_K:    1 tensors
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = SPM
llm_load_print_meta: n_vocab          = 32000
llm_load_print_meta: n_merges         = 0
llm_load_print_meta: n_ctx_train      = 32768
llm_load_print_meta: n_embd           = 4096
llm_load_print_meta: n_head           = 32
llm_load_print_meta: n_head_kv        = 8
llm_load_print_meta: n_layer          = 32
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_gqa            = 4
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
llm_load_print_meta: f_clamp_kqv      = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: n_ff             = 14336
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx  = 32768
llm_load_print_meta: rope_finetuned   = unknown
llm_load_print_meta: model type       = 7B
llm_load_print_meta: model ftype      = mostly Q4_0
llm_load_print_meta: model params     = 7.24 B
llm_load_print_meta: model size       = 3.83 GiB (4.54 BPW) 
llm_load_print_meta: general.name     = mistralai
llm_load_print_meta: BOS token        = 1 '<s>'
llm_load_print_meta: EOS token        = 2 '</s>'
llm_load_print_meta: UNK token        = 0 '<unk>'
llm_load_print_meta: LF token         = 13 '<0x0A>'
llm_load_tensors: ggml ctx size =    0.11 MiB
llm_load_tensors: mem required  = 3917.97 MiB
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llama_new_context_with_model: n_ctx      = 32768
llama_new_context_with_model: freq_base  = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_new_context_with_model: kv self size  = 4096.00 MiB
llama_build_graph: non-view tensors processed: 676/676
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M2
ggml_metal_init: picking default device: Apple M2
ggml_metal_init: default.metallib not found, loading from source
ggml_metal_init: loading '/var/folders/q5/yq5tdvb520z37pwzt2h5__2m0000gn/T/ollama1268607975/llama.cpp/gguf/build/metal/bin/ggml-metal.metal'
ggml_metal_init: GPU name:   Apple M2
ggml_metal_init: GPU family: MTLGPUFamilyApple8 (1008)
ggml_metal_init: hasUnifiedMemory              = true
ggml_metal_init: recommendedMaxWorkingSetSize  =  5461.34 MiB
ggml_metal_init: maxTransferRate               = built-in GPU
llama_new_context_with_model: compute buffer total size = 2139.07 MiB
llama_new_context_with_model: max tensor size =   102.54 MiB
ggml_metal_add_buffer: allocated 'data            ' buffer, size =  3918.58 MiB, ( 3919.20 /  5461.34)
ggml_metal_add_buffer: allocated 'kv              ' buffer, size =  4096.00 MiB, offs =            0
ggml_metal_add_buffer: allocated 'kv              ' buffer, size =     0.03 MiB, offs =   4294950912, ( 8015.23 /  5461.34)ggml_metal_add_buffer: warning: current allocated size is greater than the recommended max working set size
ggml_metal_add_buffer: allocated 'alloc           ' buffer, size =  2136.02 MiB, (10151.25 /  5461.34)ggml_metal_add_buffer: warning: current allocated size is greater than the recommended max working set size
ggml_metal_graph_compute: command buffer 0 failed with status 5
GGML_ASSERT: /Users/jmorgan/workspace/ollama/llm/llama.cpp/gguf/ggml-metal.m:1623: false
2023/12/13 13:01:19 llama.go:449: signal: abort trap
2023/12/13 13:01:19 llama.go:457: error starting llama runner: llama runner process has terminated
2023/12/13 13:01:19 llama.go:523: llama runner stopped successfully
[GIN] 2023/12/13 - 13:01:19 | 500 |   1.04335325s |       127.0.0.1 | POST     "/api/generate"

I also installed it and ran the previous commands on m2 pro and everything was fine. Is it because I'm using a m2 with 8gb? or is it because I firstly used brew?

I'd appreciate your help!

Originally created by @milioe on GitHub (Dec 13, 2023). Original GitHub issue: https://github.com/ollama/ollama/issues/1508 I'm currently running Ollama on a MacBook Air m2 (8GB) I firstly installed Ollama through `brew install ollama` and got `Error: llama runner process has terminated` after pulling and running `mistral:instruct` and `mistral:latest` . After that, I uninstalled using `brew uninstall ollama` then installing it through website. I ran the following commands: * `ollama pull mistral:instruct` * `ollama run mistral` and I got the same error: `Error: llama runner process has terminated` I checked the logs using `cat ~/.ollama/logs/server.log` and I got this: ``` 2023/12/13 13:01:18 llama.go:434: starting llama runner 2023/12/13 13:01:18 llama.go:492: waiting for llama runner to start responding {"timestamp":1702494078,"level":"INFO","function":"main","line":2656,"message":"build info","build":417,"commit":"23b5e12"} {"timestamp":1702494078,"level":"INFO","function":"main","line":2663,"message":"system info","n_threads":4,"n_threads_batch":-1,"total_threads":8,"system_info":"AVX = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 | "} llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from /Users/emiliosandoval/.ollama/models/blobs/sha256:c70fa74a8e81c3bd041cc2c30152fe6e251fdc915a3792147147a5c06bc4b309 (version GGUF V3 (latest)) llama_model_loader: - tensor 0: token_embd.weight q4_0 [ 4096, 32000, 1, 1 ] llama_model_loader: - tensor 1: blk.0.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 2: blk.0.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 3: blk.0.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 4: blk.0.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 5: blk.0.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 6: blk.0.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 7: blk.0.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 8: blk.0.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 9: blk.0.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 10: blk.1.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 11: blk.1.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 12: blk.1.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 13: blk.1.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 14: blk.1.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 15: blk.1.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 16: blk.1.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 17: blk.1.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 18: blk.1.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 19: blk.2.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 20: blk.2.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 21: blk.2.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 22: blk.2.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 23: blk.2.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 24: blk.2.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 25: blk.2.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 26: blk.2.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 27: blk.2.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 28: blk.3.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 29: blk.3.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 30: blk.3.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 31: blk.3.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 32: blk.3.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 33: blk.3.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 34: blk.3.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 35: blk.3.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 36: blk.3.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 37: blk.4.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 38: blk.4.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 39: blk.4.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 40: blk.4.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 41: blk.4.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 42: blk.4.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 43: blk.4.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 44: blk.4.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 45: blk.4.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 46: blk.5.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 47: blk.5.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 48: blk.5.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 49: blk.5.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 50: blk.5.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 51: blk.5.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 52: blk.5.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 53: blk.5.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 54: blk.5.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 55: blk.6.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 56: blk.6.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 57: blk.6.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 58: blk.6.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 59: blk.6.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 60: blk.6.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 61: blk.6.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 62: blk.6.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 63: blk.6.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 64: blk.7.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - 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tensor 78: blk.8.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 79: blk.8.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 80: blk.8.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 81: blk.8.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 82: blk.9.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 83: blk.9.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 84: blk.9.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 85: blk.9.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 86: blk.9.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 87: blk.9.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 88: blk.9.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 89: blk.9.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 90: blk.9.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 91: blk.10.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 92: blk.10.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 93: blk.10.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 94: blk.10.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 95: blk.10.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 96: blk.10.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 97: blk.10.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 98: blk.10.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 99: blk.10.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 100: blk.11.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 101: blk.11.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 102: blk.11.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 103: blk.11.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 104: blk.11.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 105: blk.11.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 106: blk.11.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 107: blk.11.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 108: blk.11.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 109: blk.12.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 110: blk.12.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 111: blk.12.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 112: blk.12.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 113: blk.12.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 114: blk.12.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 115: blk.12.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 116: blk.12.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 117: blk.12.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 118: blk.13.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 119: blk.13.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 120: blk.13.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 121: blk.13.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 122: blk.13.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 123: blk.13.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 124: blk.13.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 125: blk.13.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 126: blk.13.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 127: blk.14.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 128: blk.14.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 129: blk.14.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - 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tensor 143: blk.15.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 144: blk.15.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 145: blk.16.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 146: blk.16.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 147: blk.16.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 148: blk.16.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 149: blk.16.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 150: blk.16.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 151: blk.16.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 152: blk.16.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 153: blk.16.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 154: blk.17.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 155: blk.17.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - 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tensor 234: blk.25.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 235: blk.26.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 236: blk.26.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 237: blk.26.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 238: blk.26.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 239: blk.26.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 240: blk.26.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 241: blk.26.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 242: blk.26.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 243: blk.26.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 244: blk.27.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 245: blk.27.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 246: blk.27.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 247: blk.27.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 248: blk.27.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 249: blk.27.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 250: blk.27.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 251: blk.27.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 252: blk.27.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 253: blk.28.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 254: blk.28.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 255: blk.28.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 256: blk.28.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 257: blk.28.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 258: blk.28.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 259: blk.28.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 260: blk.28.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 261: blk.28.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 262: blk.29.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 263: blk.29.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 264: blk.29.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 265: blk.29.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 266: blk.29.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 267: blk.29.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 268: blk.29.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 269: blk.29.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 270: blk.29.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 271: blk.30.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 272: blk.30.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 273: blk.30.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 274: blk.30.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 275: blk.30.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 276: blk.30.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 277: blk.30.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 278: blk.30.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 279: blk.30.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 280: blk.31.attn_q.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 281: blk.31.attn_k.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 282: blk.31.attn_v.weight q4_0 [ 4096, 1024, 1, 1 ] llama_model_loader: - tensor 283: blk.31.attn_output.weight q4_0 [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 284: blk.31.ffn_gate.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 285: blk.31.ffn_up.weight q4_0 [ 4096, 14336, 1, 1 ] llama_model_loader: - tensor 286: blk.31.ffn_down.weight q4_0 [ 14336, 4096, 1, 1 ] llama_model_loader: - tensor 287: blk.31.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 288: blk.31.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 289: output_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 290: output.weight q6_K [ 4096, 32000, 1, 1 ] llama_model_loader: - kv 0: general.architecture str = llama llama_model_loader: - kv 1: general.name str = mistralai llama_model_loader: - kv 2: llama.context_length u32 = 32768 llama_model_loader: - kv 3: llama.embedding_length u32 = 4096 llama_model_loader: - kv 4: llama.block_count u32 = 32 llama_model_loader: - kv 5: llama.feed_forward_length u32 = 14336 llama_model_loader: - kv 6: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 7: llama.attention.head_count u32 = 32 llama_model_loader: - kv 8: llama.attention.head_count_kv u32 = 8 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000010 llama_model_loader: - kv 10: llama.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 11: general.file_type u32 = 2 llama_model_loader: - kv 12: tokenizer.ggml.model str = llama llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,32000] = ["<unk>", "<s>", "</s>", "<0x00>", "<... llama_model_loader: - kv 14: tokenizer.ggml.scores arr[f32,32000] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 15: tokenizer.ggml.token_type arr[i32,32000] = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ... llama_model_loader: - kv 16: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 17: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 18: tokenizer.ggml.unknown_token_id u32 = 0 llama_model_loader: - kv 19: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 20: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 21: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q4_0: 225 tensors llama_model_loader: - type q6_K: 1 tensors llm_load_vocab: special tokens definition check successful ( 259/32000 ). llm_load_print_meta: format = GGUF V3 (latest) llm_load_print_meta: arch = llama llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 32000 llm_load_print_meta: n_merges = 0 llm_load_print_meta: n_ctx_train = 32768 llm_load_print_meta: n_embd = 4096 llm_load_print_meta: n_head = 32 llm_load_print_meta: n_head_kv = 8 llm_load_print_meta: n_layer = 32 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_gqa = 4 llm_load_print_meta: f_norm_eps = 0.0e+00 llm_load_print_meta: f_norm_rms_eps = 1.0e-05 llm_load_print_meta: f_clamp_kqv = 0.0e+00 llm_load_print_meta: f_max_alibi_bias = 0.0e+00 llm_load_print_meta: n_ff = 14336 llm_load_print_meta: rope scaling = linear llm_load_print_meta: freq_base_train = 1000000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_yarn_orig_ctx = 32768 llm_load_print_meta: rope_finetuned = unknown llm_load_print_meta: model type = 7B llm_load_print_meta: model ftype = mostly Q4_0 llm_load_print_meta: model params = 7.24 B llm_load_print_meta: model size = 3.83 GiB (4.54 BPW) llm_load_print_meta: general.name = mistralai llm_load_print_meta: BOS token = 1 '<s>' llm_load_print_meta: EOS token = 2 '</s>' llm_load_print_meta: UNK token = 0 '<unk>' llm_load_print_meta: LF token = 13 '<0x0A>' llm_load_tensors: ggml ctx size = 0.11 MiB llm_load_tensors: mem required = 3917.97 MiB .......... ..................... ............... .............. ........... ......... ........ ...... .... llama_new_context_with_model: n_ctx = 32768 llama_new_context_with_model: freq_base = 1000000.0 llama_new_context_with_model: freq_scale = 1 llama_new_context_with_model: kv self size = 4096.00 MiB llama_build_graph: non-view tensors processed: 676/676 ggml_metal_init: allocating ggml_metal_init: found device: Apple M2 ggml_metal_init: picking default device: Apple M2 ggml_metal_init: default.metallib not found, loading from source ggml_metal_init: loading '/var/folders/q5/yq5tdvb520z37pwzt2h5__2m0000gn/T/ollama1268607975/llama.cpp/gguf/build/metal/bin/ggml-metal.metal' ggml_metal_init: GPU name: Apple M2 ggml_metal_init: GPU family: MTLGPUFamilyApple8 (1008) ggml_metal_init: hasUnifiedMemory = true ggml_metal_init: recommendedMaxWorkingSetSize = 5461.34 MiB ggml_metal_init: maxTransferRate = built-in GPU llama_new_context_with_model: compute buffer total size = 2139.07 MiB llama_new_context_with_model: max tensor size = 102.54 MiB ggml_metal_add_buffer: allocated 'data ' buffer, size = 3918.58 MiB, ( 3919.20 / 5461.34) ggml_metal_add_buffer: allocated 'kv ' buffer, size = 4096.00 MiB, offs = 0 ggml_metal_add_buffer: allocated 'kv ' buffer, size = 0.03 MiB, offs = 4294950912, ( 8015.23 / 5461.34)ggml_metal_add_buffer: warning: current allocated size is greater than the recommended max working set size ggml_metal_add_buffer: allocated 'alloc ' buffer, size = 2136.02 MiB, (10151.25 / 5461.34)ggml_metal_add_buffer: warning: current allocated size is greater than the recommended max working set size ggml_metal_graph_compute: command buffer 0 failed with status 5 GGML_ASSERT: /Users/jmorgan/workspace/ollama/llm/llama.cpp/gguf/ggml-metal.m:1623: false 2023/12/13 13:01:19 llama.go:449: signal: abort trap 2023/12/13 13:01:19 llama.go:457: error starting llama runner: llama runner process has terminated 2023/12/13 13:01:19 llama.go:523: llama runner stopped successfully [GIN] 2023/12/13 - 13:01:19 | 500 | 1.04335325s | 127.0.0.1 | POST "/api/generate" ``` I also installed it and ran the previous commands on m2 pro and everything was fine. Is it because I'm using a m2 with 8gb? or is it because I firstly used `brew`? I'd appreciate your help!
GiteaMirror commented 2026-04-12 10:29:37 -05:00
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@igorschlum commented on GitHub (Dec 13, 2023):

I think it's because you have only 8GB of memory.

<!-- gh-comment-id:1854843417 --> @igorschlum commented on GitHub (Dec 13, 2023): I think it's because you have only 8GB of memory.
GiteaMirror commented 2026-04-12 10:29:38 -05:00
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@easp commented on GitHub (Dec 14, 2023):

I think it's because you have only 8GB of memory.

Definitely. From the log

(10151.25 / 5461.34)ggml_metal_add_buffer: warning: current allocated size is greater than the recommended max working set size

Needs 10151MB, only has 5461MB available for use.

<!-- gh-comment-id:1855083385 --> @easp commented on GitHub (Dec 14, 2023): > I think it's because you have only 8GB of memory. Definitely. From the log > (10151.25 / 5461.34)ggml_metal_add_buffer: warning: current allocated size is greater than the recommended max working set size Needs 10151MB, only has 5461MB available for use.
GiteaMirror commented 2026-04-12 10:29:38 -05:00
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@milioe commented on GitHub (Dec 14, 2023):

didn't read that part, thanks a lot! @igorschlum @easp

<!-- gh-comment-id:1855111069 --> @milioe commented on GitHub (Dec 14, 2023): didn't read that part, thanks a lot! @igorschlum @easp
GiteaMirror commented 2026-04-12 10:29:38 -05:00
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@logiota commented on GitHub (Dec 17, 2023):

Theoretically Mixtral should be a 2x7b for for actual inference, but here it asks for ram for all llm's...
is there any way to change that?
ggml_metal_add_buffer: allocated 'alloc ' buffer, size = 2164.05 MiB, (31580.89 / 21845.34)ggml_metal_add_buffer: warning: current allocated size is greater than the recommended max working set size

<!-- gh-comment-id:1859150636 --> @logiota commented on GitHub (Dec 17, 2023): Theoretically Mixtral should be a 2x7b for for actual inference, but here it asks for ram for all llm's... is there any way to change that? ggml_metal_add_buffer: allocated 'alloc ' buffer, size = 2164.05 MiB, (31580.89 / 21845.34)ggml_metal_add_buffer: warning: current allocated size is greater than the recommended max working set size
GiteaMirror commented 2026-04-12 10:29:38 -05:00
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@easp commented on GitHub (Dec 17, 2023):

Theoretically Mixtral should be a 2x7b for for actual inference, but here it asks for ram for all llm's

@logiota. That's not how it works. It chooses two experts for every layer and has to process all the layers for each token. It may well use all the experts to generate each token. Only using two at a time reduces computation & memory bandwidth requirements, but RAM is still needed for all the experts in order to have reasonable performance.

In theory it should be possible to dramatically compress the RAM footprint because the experts are more alike than they are different, but I don't think anyone has implemented this optimization yet.

<!-- gh-comment-id:1859210363 --> @easp commented on GitHub (Dec 17, 2023): > Theoretically Mixtral should be a 2x7b for for actual inference, but here it asks for ram for all llm's @logiota. That's not how it works. It chooses two experts for every layer and has to process all the layers for each token. It may well use all the experts to generate each token. Only using two at a time reduces computation & memory bandwidth requirements, but RAM is still needed for all the experts in order to have reasonable performance. In theory it should be possible to dramatically compress the RAM footprint because the experts are more alike than they are different, but I don't think anyone has implemented this optimization yet.
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