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[GH-ISSUE #10426] ollama for amd #68910

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opened 2026-05-04 15:37:40 -05:00 by GiteaMirror · 2 comments
GiteaMirror commented 2026-05-04 15:37:40 -05:00
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Originally created by @juca-12 on GitHub (Apr 26, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/10426

What is the issue?

I went to use ollama and saw that it had support for my gpu (RX6800XT) but when I went to use it it was only using the CPU instead of the GPU. Do you have any tips or solutions for this?

Relevant log output

2025/04/26 18:35:56 routes.go:1232: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:2048 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:C:\\Users\\allan\\.ollama\\models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]"
time=2025-04-26T18:35:56.037-03:00 level=INFO source=images.go:458 msg="total blobs: 13"
time=2025-04-26T18:35:56.038-03:00 level=INFO source=images.go:465 msg="total unused blobs removed: 0"
time=2025-04-26T18:35:56.039-03:00 level=INFO source=routes.go:1299 msg="Listening on 127.0.0.1:11434 (version 0.6.6)"
time=2025-04-26T18:35:56.039-03:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
time=2025-04-26T18:35:56.039-03:00 level=INFO source=gpu_windows.go:167 msg=packages count=1
time=2025-04-26T18:35:56.039-03:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=8 efficiency=0 threads=16
time=2025-04-26T18:35:56.441-03:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=rocm variant="" compute=gfx1030 driver=6.3 name="AMD Radeon RX 6800 XT" total="16.0 GiB" available="15.8 GiB"
[GIN] 2025/04/26 - 18:41:10 | 200 |      2.1605ms |       127.0.0.1 | GET      "/api/tags"
time=2025-04-26T18:48:13.873-03:00 level=WARN source=ggml.go:152 msg="key not found" key=general.alignment default=32
time=2025-04-26T18:48:14.401-03:00 level=INFO source=sched.go:187 msg="one or more GPUs detected that are unable to accurately report free memory - disabling default concurrency"
time=2025-04-26T18:48:14.410-03:00 level=WARN source=ggml.go:152 msg="key not found" key=general.alignment default=32
time=2025-04-26T18:48:14.418-03:00 level=WARN source=ggml.go:152 msg="key not found" key=general.alignment default=32
time=2025-04-26T18:48:14.418-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0
time=2025-04-26T18:48:14.419-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0
time=2025-04-26T18:48:14.420-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0
time=2025-04-26T18:48:14.420-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0
time=2025-04-26T18:48:14.838-03:00 level=INFO source=server.go:105 msg="system memory" total="31.9 GiB" free="17.2 GiB" free_swap="21.6 GiB"
time=2025-04-26T18:48:14.838-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0
time=2025-04-26T18:48:14.839-03:00 level=INFO source=server.go:138 msg=offload library=rocm layers.requested=-1 layers.model=28 layers.offload=15 layers.split="" memory.available="[15.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="26.3 GiB" memory.required.partial="15.2 GiB" memory.required.kv="8.4 GiB" memory.required.allocations="[15.2 GiB]" memory.weights.total="15.5 GiB" memory.weights.repeating="15.1 GiB" memory.weights.nonrepeating="400.0 MiB" memory.graph.full="1.1 GiB" memory.graph.partial="1.5 GiB"
llama_model_loader: loaded meta data with 42 key-value pairs and 377 tensors from C:\Users\allan\.ollama\models\blobs\sha256-c41b0dbf1599296ba76343b942c39691a96a20ff382dad8cfc674889360d773e (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = deepseek2
llama_model_loader: - kv   1:                               general.name str              = DeepSeek-Coder-V2-Lite-Instruct
llama_model_loader: - kv   2:                      deepseek2.block_count u32              = 27
llama_model_loader: - kv   3:                   deepseek2.context_length u32              = 163840
llama_model_loader: - kv   4:                 deepseek2.embedding_length u32              = 2048
llama_model_loader: - kv   5:              deepseek2.feed_forward_length u32              = 10944
llama_model_loader: - kv   6:             deepseek2.attention.head_count u32              = 16
llama_model_loader: - kv   7:          deepseek2.attention.head_count_kv u32              = 16
llama_model_loader: - kv   8:                   deepseek2.rope.freq_base f32              = 10000.000000
llama_model_loader: - kv   9: deepseek2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  10:                deepseek2.expert_used_count u32              = 6
llama_model_loader: - kv  11:                          general.file_type u32              = 7
llama_model_loader: - kv  12:        deepseek2.leading_dense_block_count u32              = 1
llama_model_loader: - kv  13:                       deepseek2.vocab_size u32              = 102400
llama_model_loader: - kv  14:           deepseek2.attention.kv_lora_rank u32              = 512
llama_model_loader: - kv  15:             deepseek2.attention.key_length u32              = 192
llama_model_loader: - kv  16:           deepseek2.attention.value_length u32              = 128
llama_model_loader: - kv  17:       deepseek2.expert_feed_forward_length u32              = 1408
llama_model_loader: - kv  18:                     deepseek2.expert_count u32              = 64
llama_model_loader: - kv  19:              deepseek2.expert_shared_count u32              = 2
llama_model_loader: - kv  20:             deepseek2.expert_weights_scale f32              = 1.000000
llama_model_loader: - kv  21:             deepseek2.rope.dimension_count u32              = 64
llama_model_loader: - kv  22:                deepseek2.rope.scaling.type str              = yarn
llama_model_loader: - kv  23:              deepseek2.rope.scaling.factor f32              = 40.000000
llama_model_loader: - kv  24: deepseek2.rope.scaling.original_context_length u32              = 4096
llama_model_loader: - kv  25: deepseek2.rope.scaling.yarn_log_multiplier f32              = 0.070700
llama_model_loader: - kv  26:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  27:                         tokenizer.ggml.pre str              = deepseek-llm
llama_model_loader: - kv  28:                      tokenizer.ggml.tokens arr[str,102400]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  29:                  tokenizer.ggml.token_type arr[i32,102400]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  30:                      tokenizer.ggml.merges arr[str,99757]   = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "h e...
llama_model_loader: - kv  31:                tokenizer.ggml.bos_token_id u32              = 100000
llama_model_loader: - kv  32:                tokenizer.ggml.eos_token_id u32              = 100001
llama_model_loader: - kv  33:            tokenizer.ggml.padding_token_id u32              = 100001
llama_model_loader: - kv  34:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  35:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  36:                    tokenizer.chat_template str              = {% if not add_generation_prompt is de...
llama_model_loader: - kv  37:               general.quantization_version u32              = 2
llama_model_loader: - kv  38:                      quantize.imatrix.file str              = /models/DeepSeek-Coder-V2-Lite-Instru...
llama_model_loader: - kv  39:                   quantize.imatrix.dataset str              = /training_data/calibration_datav3.txt
llama_model_loader: - kv  40:             quantize.imatrix.entries_count i32              = 293
llama_model_loader: - kv  41:              quantize.imatrix.chunks_count i32              = 139
llama_model_loader: - type  f32:  108 tensors
llama_model_loader: - type  f16:    2 tensors
llama_model_loader: - type q8_0:  267 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q8_0
print_info: file size   = 15.92 GiB (8.71 BPW) 
load: control-looking token: 100002 '<｜fim▁hole｜>' was not control-type; this is probably a bug in the model. its type will be overridden
load: control-looking token: 100004 '<｜fim▁end｜>' was not control-type; this is probably a bug in the model. its type will be overridden
load: control-looking token: 100003 '<｜fim▁begin｜>' was not control-type; this is probably a bug in the model. its type will be overridden
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 2400
load: token to piece cache size = 0.6661 MB
print_info: arch             = deepseek2
print_info: vocab_only       = 1
print_info: model type       = ?B
print_info: model params     = 15.71 B
print_info: general.name     = DeepSeek-Coder-V2-Lite-Instruct
print_info: n_layer_dense_lead   = 0
print_info: n_lora_q             = 0
print_info: n_lora_kv            = 0
print_info: n_ff_exp             = 0
print_info: n_expert_shared      = 0
print_info: expert_weights_scale = 0.0
print_info: expert_weights_norm  = 0
print_info: expert_gating_func   = unknown
print_info: rope_yarn_log_mul    = 0.0000
print_info: vocab type       = BPE
print_info: n_vocab          = 102400
print_info: n_merges         = 99757
print_info: BOS token        = 100000 '<｜begin▁of▁sentence｜>'
print_info: EOS token        = 100001 '<｜end▁of▁sentence｜>'
print_info: EOT token        = 100001 '<｜end▁of▁sentence｜>'
print_info: PAD token        = 100001 '<｜end▁of▁sentence｜>'
print_info: LF token         = 185 'Ċ'
print_info: FIM PRE token    = 100003 '<｜fim▁begin｜>'
print_info: FIM SUF token    = 100002 '<｜fim▁hole｜>'
print_info: FIM MID token    = 100004 '<｜fim▁end｜>'
print_info: EOG token        = 100001 '<｜end▁of▁sentence｜>'
print_info: max token length = 256
llama_model_load: vocab only - skipping tensors
time=2025-04-26T18:48:14.953-03:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\allan\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\allan\\.ollama\\models\\blobs\\sha256-c41b0dbf1599296ba76343b942c39691a96a20ff382dad8cfc674889360d773e --ctx-size 32768 --batch-size 512 --n-gpu-layers 15 --threads 8 --parallel 1 --port 64270"
time=2025-04-26T18:48:14.956-03:00 level=INFO source=sched.go:451 msg="loaded runners" count=1
time=2025-04-26T18:48:14.956-03:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding"
time=2025-04-26T18:48:14.957-03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error"
time=2025-04-26T18:48:14.987-03:00 level=INFO source=runner.go:853 msg="starting go runner"
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon RX 6800 XT, gfx1030 (0x1030), VMM: no, Wave Size: 32
load_backend: loaded ROCm backend from C:\Users\allan\AppData\Local\Programs\Ollama\lib\ollama\rocm\ggml-hip.dll
load_backend: loaded CPU backend from C:\Users\allan\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll
time=2025-04-26T18:48:15.195-03:00 level=INFO source=ggml.go:109 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.NO_PEER_COPY=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang)
time=2025-04-26T18:48:15.196-03:00 level=INFO source=runner.go:913 msg="Server listening on 127.0.0.1:64270"
time=2025-04-26T18:48:15.207-03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model"
llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon RX 6800 XT) - 16226 MiB free
llama_model_loader: loaded meta data with 42 key-value pairs and 377 tensors from C:\Users\allan\.ollama\models\blobs\sha256-c41b0dbf1599296ba76343b942c39691a96a20ff382dad8cfc674889360d773e (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = deepseek2
llama_model_loader: - kv   1:                               general.name str              = DeepSeek-Coder-V2-Lite-Instruct
llama_model_loader: - kv   2:                      deepseek2.block_count u32              = 27
llama_model_loader: - kv   3:                   deepseek2.context_length u32              = 163840
llama_model_loader: - kv   4:                 deepseek2.embedding_length u32              = 2048
llama_model_loader: - kv   5:              deepseek2.feed_forward_length u32              = 10944
llama_model_loader: - kv   6:             deepseek2.attention.head_count u32              = 16
llama_model_loader: - kv   7:          deepseek2.attention.head_count_kv u32              = 16
llama_model_loader: - kv   8:                   deepseek2.rope.freq_base f32              = 10000.000000
llama_model_loader: - kv   9: deepseek2.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  10:                deepseek2.expert_used_count u32              = 6
llama_model_loader: - kv  11:                          general.file_type u32              = 7
llama_model_loader: - kv  12:        deepseek2.leading_dense_block_count u32              = 1
llama_model_loader: - kv  13:                       deepseek2.vocab_size u32              = 102400
llama_model_loader: - kv  14:           deepseek2.attention.kv_lora_rank u32              = 512
llama_model_loader: - kv  15:             deepseek2.attention.key_length u32              = 192
llama_model_loader: - kv  16:           deepseek2.attention.value_length u32              = 128
llama_model_loader: - kv  17:       deepseek2.expert_feed_forward_length u32              = 1408
llama_model_loader: - kv  18:                     deepseek2.expert_count u32              = 64
llama_model_loader: - kv  19:              deepseek2.expert_shared_count u32              = 2
llama_model_loader: - kv  20:             deepseek2.expert_weights_scale f32              = 1.000000
llama_model_loader: - kv  21:             deepseek2.rope.dimension_count u32              = 64
llama_model_loader: - kv  22:                deepseek2.rope.scaling.type str              = yarn
llama_model_loader: - kv  23:              deepseek2.rope.scaling.factor f32              = 40.000000
llama_model_loader: - kv  24: deepseek2.rope.scaling.original_context_length u32              = 4096
llama_model_loader: - kv  25: deepseek2.rope.scaling.yarn_log_multiplier f32              = 0.070700
llama_model_loader: - kv  26:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  27:                         tokenizer.ggml.pre str              = deepseek-llm
llama_model_loader: - kv  28:                      tokenizer.ggml.tokens arr[str,102400]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  29:                  tokenizer.ggml.token_type arr[i32,102400]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  30:                      tokenizer.ggml.merges arr[str,99757]   = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "h e...
llama_model_loader: - kv  31:                tokenizer.ggml.bos_token_id u32              = 100000
llama_model_loader: - kv  32:                tokenizer.ggml.eos_token_id u32              = 100001
llama_model_loader: - kv  33:            tokenizer.ggml.padding_token_id u32              = 100001
llama_model_loader: - kv  34:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  35:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - kv  36:                    tokenizer.chat_template str              = {% if not add_generation_prompt is de...
llama_model_loader: - kv  37:               general.quantization_version u32              = 2
llama_model_loader: - kv  38:                      quantize.imatrix.file str              = /models/DeepSeek-Coder-V2-Lite-Instru...
llama_model_loader: - kv  39:                   quantize.imatrix.dataset str              = /training_data/calibration_datav3.txt
llama_model_loader: - kv  40:             quantize.imatrix.entries_count i32              = 293
llama_model_loader: - kv  41:              quantize.imatrix.chunks_count i32              = 139
llama_model_loader: - type  f32:  108 tensors
llama_model_loader: - type  f16:    2 tensors
llama_model_loader: - type q8_0:  267 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q8_0
print_info: file size   = 15.92 GiB (8.71 BPW) 
load: control-looking token: 100002 '<｜fim▁hole｜>' was not control-type; this is probably a bug in the model. its type will be overridden
load: control-looking token: 100004 '<｜fim▁end｜>' was not control-type; this is probably a bug in the model. its type will be overridden
load: control-looking token: 100003 '<｜fim▁begin｜>' was not control-type; this is probably a bug in the model. its type will be overridden
load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect
load: special tokens cache size = 2400
load: token to piece cache size = 0.6661 MB
print_info: arch             = deepseek2
print_info: vocab_only       = 0
print_info: n_ctx_train      = 163840
print_info: n_embd           = 2048
print_info: n_layer          = 27
print_info: n_head           = 16
print_info: n_head_kv        = 16
print_info: n_rot            = 64
print_info: n_swa            = 0
print_info: n_swa_pattern    = 1
print_info: n_embd_head_k    = 192
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 1
print_info: n_embd_k_gqa     = 3072
print_info: n_embd_v_gqa     = 2048
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-06
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: f_attn_scale     = 0.0e+00
print_info: n_ff             = 10944
print_info: n_expert         = 64
print_info: n_expert_used    = 6
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 0
print_info: rope scaling     = yarn
print_info: freq_base_train  = 10000.0
print_info: freq_scale_train = 0.025
print_info: n_ctx_orig_yarn  = 4096
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 16B
print_info: model params     = 15.71 B
print_info: general.name     = DeepSeek-Coder-V2-Lite-Instruct
print_info: n_layer_dense_lead   = 1
print_info: n_lora_q             = 0
print_info: n_lora_kv            = 512
print_info: n_ff_exp             = 1408
print_info: n_expert_shared      = 2
print_info: expert_weights_scale = 1.0
print_info: expert_weights_norm  = 0
print_info: expert_gating_func   = softmax
print_info: rope_yarn_log_mul    = 0.0707
print_info: vocab type       = BPE
print_info: n_vocab          = 102400
print_info: n_merges         = 99757
print_info: BOS token        = 100000 '<｜begin▁of▁sentence｜>'
print_info: EOS token        = 100001 '<｜end▁of▁sentence｜>'
print_info: EOT token        = 100001 '<｜end▁of▁sentence｜>'
print_info: PAD token        = 100001 '<｜end▁of▁sentence｜>'
print_info: LF token         = 185 'Ċ'
print_info: FIM PRE token    = 100003 '<｜fim▁begin｜>'
print_info: FIM SUF token    = 100002 '<｜fim▁hole｜>'
print_info: FIM MID token    = 100004 '<｜fim▁end｜>'
print_info: EOG token        = 100001 '<｜end▁of▁sentence｜>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 15 repeating layers to GPU
load_tensors: offloaded 15/28 layers to GPU
load_tensors:        ROCm0 model buffer size =  8894.92 MiB
load_tensors:   CPU_Mapped model buffer size =  8623.01 MiB
llama_context: constructing llama_context
llama_context: n_seq_max     = 1
llama_context: n_ctx         = 32768
llama_context: n_ctx_per_seq = 32768
llama_context: n_batch       = 512
llama_context: n_ubatch      = 512
llama_context: causal_attn   = 1
llama_context: flash_attn    = 0
llama_context: freq_base     = 10000.0
llama_context: freq_scale    = 0.025
llama_context: n_ctx_per_seq (32768) < n_ctx_train (163840) -- the full capacity of the model will not be utilized
llama_context:        CPU  output buffer size =     0.40 MiB
init: kv_size = 32768, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 27, can_shift = 0
init:      ROCm0 KV buffer size =  4800.00 MiB
init:        CPU KV buffer size =  3840.00 MiB
llama_context: KV self size  = 8640.00 MiB, K (f16): 5184.00 MiB, V (f16): 3456.00 MiB
llama_context:      ROCm0 compute buffer size =  1434.38 MiB
llama_context:  ROCm_Host compute buffer size =    74.01 MiB
llama_context: graph nodes  = 1951
llama_context: graph splits = 192 (with bs=512), 3 (with bs=1)
time=2025-04-26T18:49:03.050-03:00 level=INFO source=server.go:619 msg="llama runner started in 48.09 seconds"
[GIN] 2025/04/26 - 18:49:37 | 200 |         1m23s |       127.0.0.1 | POST     "/api/chat"
time=2025-04-26T18:49:38.086-03:00 level=WARN source=ggml.go:152 msg="key not found" key=general.alignment default=32
[GIN] 2025/04/26 - 18:50:41 | 200 |          1m3s |       127.0.0.1 | POST     "/api/chat"

OS

Windows

GPU

AMD

CPU

No response

Ollama version

No response

Originally created by @juca-12 on GitHub (Apr 26, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/10426 ### What is the issue? I went to use ollama and saw that it had support for my gpu (RX6800XT) but when I went to use it it was only using the CPU instead of the GPU. Do you have any tips or solutions for this? ### Relevant log output ```shell 2025/04/26 18:35:56 routes.go:1232: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: HTTPS_PROXY: HTTP_PROXY: NO_PROXY: OLLAMA_CONTEXT_LENGTH:2048 OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_GPU_OVERHEAD:0 OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_KV_CACHE_TYPE: OLLAMA_LLM_LIBRARY: OLLAMA_LOAD_TIMEOUT:5m0s OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:C:\\Users\\allan\\.ollama\\models OLLAMA_MULTIUSER_CACHE:false OLLAMA_NEW_ENGINE:false OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://* vscode-webview://* vscode-file://*] OLLAMA_SCHED_SPREAD:false ROCR_VISIBLE_DEVICES:]" time=2025-04-26T18:35:56.037-03:00 level=INFO source=images.go:458 msg="total blobs: 13" time=2025-04-26T18:35:56.038-03:00 level=INFO source=images.go:465 msg="total unused blobs removed: 0" time=2025-04-26T18:35:56.039-03:00 level=INFO source=routes.go:1299 msg="Listening on 127.0.0.1:11434 (version 0.6.6)" time=2025-04-26T18:35:56.039-03:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs" time=2025-04-26T18:35:56.039-03:00 level=INFO source=gpu_windows.go:167 msg=packages count=1 time=2025-04-26T18:35:56.039-03:00 level=INFO source=gpu_windows.go:214 msg="" package=0 cores=8 efficiency=0 threads=16 time=2025-04-26T18:35:56.441-03:00 level=INFO source=types.go:130 msg="inference compute" id=0 library=rocm variant="" compute=gfx1030 driver=6.3 name="AMD Radeon RX 6800 XT" total="16.0 GiB" available="15.8 GiB" [GIN] 2025/04/26 - 18:41:10 | 200 | 2.1605ms | 127.0.0.1 | GET "/api/tags" time=2025-04-26T18:48:13.873-03:00 level=WARN source=ggml.go:152 msg="key not found" key=general.alignment default=32 time=2025-04-26T18:48:14.401-03:00 level=INFO source=sched.go:187 msg="one or more GPUs detected that are unable to accurately report free memory - disabling default concurrency" time=2025-04-26T18:48:14.410-03:00 level=WARN source=ggml.go:152 msg="key not found" key=general.alignment default=32 time=2025-04-26T18:48:14.418-03:00 level=WARN source=ggml.go:152 msg="key not found" key=general.alignment default=32 time=2025-04-26T18:48:14.418-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0 time=2025-04-26T18:48:14.419-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0 time=2025-04-26T18:48:14.420-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0 time=2025-04-26T18:48:14.420-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0 time=2025-04-26T18:48:14.838-03:00 level=INFO source=server.go:105 msg="system memory" total="31.9 GiB" free="17.2 GiB" free_swap="21.6 GiB" time=2025-04-26T18:48:14.838-03:00 level=WARN source=ggml.go:152 msg="key not found" key=deepseek2.vision.block_count default=0 time=2025-04-26T18:48:14.839-03:00 level=INFO source=server.go:138 msg=offload library=rocm layers.requested=-1 layers.model=28 layers.offload=15 layers.split="" memory.available="[15.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="26.3 GiB" memory.required.partial="15.2 GiB" memory.required.kv="8.4 GiB" memory.required.allocations="[15.2 GiB]" memory.weights.total="15.5 GiB" memory.weights.repeating="15.1 GiB" memory.weights.nonrepeating="400.0 MiB" memory.graph.full="1.1 GiB" memory.graph.partial="1.5 GiB" llama_model_loader: loaded meta data with 42 key-value pairs and 377 tensors from C:\Users\allan\.ollama\models\blobs\sha256-c41b0dbf1599296ba76343b942c39691a96a20ff382dad8cfc674889360d773e (version GGUF V3 (latest)) llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. llama_model_loader: - kv 0: general.architecture str = deepseek2 llama_model_loader: - kv 1: general.name str = DeepSeek-Coder-V2-Lite-Instruct llama_model_loader: - kv 2: deepseek2.block_count u32 = 27 llama_model_loader: - kv 3: deepseek2.context_length u32 = 163840 llama_model_loader: - kv 4: deepseek2.embedding_length u32 = 2048 llama_model_loader: - kv 5: deepseek2.feed_forward_length u32 = 10944 llama_model_loader: - kv 6: deepseek2.attention.head_count u32 = 16 llama_model_loader: - kv 7: deepseek2.attention.head_count_kv u32 = 16 llama_model_loader: - kv 8: deepseek2.rope.freq_base f32 = 10000.000000 llama_model_loader: - kv 9: deepseek2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 10: deepseek2.expert_used_count u32 = 6 llama_model_loader: - kv 11: general.file_type u32 = 7 llama_model_loader: - kv 12: deepseek2.leading_dense_block_count u32 = 1 llama_model_loader: - kv 13: deepseek2.vocab_size u32 = 102400 llama_model_loader: - kv 14: deepseek2.attention.kv_lora_rank u32 = 512 llama_model_loader: - kv 15: deepseek2.attention.key_length u32 = 192 llama_model_loader: - kv 16: deepseek2.attention.value_length u32 = 128 llama_model_loader: - kv 17: deepseek2.expert_feed_forward_length u32 = 1408 llama_model_loader: - kv 18: deepseek2.expert_count u32 = 64 llama_model_loader: - kv 19: deepseek2.expert_shared_count u32 = 2 llama_model_loader: - kv 20: deepseek2.expert_weights_scale f32 = 1.000000 llama_model_loader: - kv 21: deepseek2.rope.dimension_count u32 = 64 llama_model_loader: - kv 22: deepseek2.rope.scaling.type str = yarn llama_model_loader: - kv 23: deepseek2.rope.scaling.factor f32 = 40.000000 llama_model_loader: - kv 24: deepseek2.rope.scaling.original_context_length u32 = 4096 llama_model_loader: - kv 25: deepseek2.rope.scaling.yarn_log_multiplier f32 = 0.070700 llama_model_loader: - kv 26: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 27: tokenizer.ggml.pre str = deepseek-llm llama_model_loader: - kv 28: tokenizer.ggml.tokens arr[str,102400] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 29: tokenizer.ggml.token_type arr[i32,102400] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 30: tokenizer.ggml.merges arr[str,99757] = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "h e... llama_model_loader: - kv 31: tokenizer.ggml.bos_token_id u32 = 100000 llama_model_loader: - kv 32: tokenizer.ggml.eos_token_id u32 = 100001 llama_model_loader: - kv 33: tokenizer.ggml.padding_token_id u32 = 100001 llama_model_loader: - kv 34: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 35: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 36: tokenizer.chat_template str = {% if not add_generation_prompt is de... llama_model_loader: - kv 37: general.quantization_version u32 = 2 llama_model_loader: - kv 38: quantize.imatrix.file str = /models/DeepSeek-Coder-V2-Lite-Instru... llama_model_loader: - kv 39: quantize.imatrix.dataset str = /training_data/calibration_datav3.txt llama_model_loader: - kv 40: quantize.imatrix.entries_count i32 = 293 llama_model_loader: - kv 41: quantize.imatrix.chunks_count i32 = 139 llama_model_loader: - type f32: 108 tensors llama_model_loader: - type f16: 2 tensors llama_model_loader: - type q8_0: 267 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q8_0 print_info: file size = 15.92 GiB (8.71 BPW) load: control-looking token: 100002 '<｜fim▁hole｜>' was not control-type; this is probably a bug in the model. its type will be overridden load: control-looking token: 100004 '<｜fim▁end｜>' was not control-type; this is probably a bug in the model. its type will be overridden load: control-looking token: 100003 '<｜fim▁begin｜>' was not control-type; this is probably a bug in the model. its type will be overridden load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect load: special tokens cache size = 2400 load: token to piece cache size = 0.6661 MB print_info: arch = deepseek2 print_info: vocab_only = 1 print_info: model type = ?B print_info: model params = 15.71 B print_info: general.name = DeepSeek-Coder-V2-Lite-Instruct print_info: n_layer_dense_lead = 0 print_info: n_lora_q = 0 print_info: n_lora_kv = 0 print_info: n_ff_exp = 0 print_info: n_expert_shared = 0 print_info: expert_weights_scale = 0.0 print_info: expert_weights_norm = 0 print_info: expert_gating_func = unknown print_info: rope_yarn_log_mul = 0.0000 print_info: vocab type = BPE print_info: n_vocab = 102400 print_info: n_merges = 99757 print_info: BOS token = 100000 '<｜begin▁of▁sentence｜>' print_info: EOS token = 100001 '<｜end▁of▁sentence｜>' print_info: EOT token = 100001 '<｜end▁of▁sentence｜>' print_info: PAD token = 100001 '<｜end▁of▁sentence｜>' print_info: LF token = 185 'Ċ' print_info: FIM PRE token = 100003 '<｜fim▁begin｜>' print_info: FIM SUF token = 100002 '<｜fim▁hole｜>' print_info: FIM MID token = 100004 '<｜fim▁end｜>' print_info: EOG token = 100001 '<｜end▁of▁sentence｜>' print_info: max token length = 256 llama_model_load: vocab only - skipping tensors time=2025-04-26T18:48:14.953-03:00 level=INFO source=server.go:405 msg="starting llama server" cmd="C:\\Users\\allan\\AppData\\Local\\Programs\\Ollama\\ollama.exe runner --model C:\\Users\\allan\\.ollama\\models\\blobs\\sha256-c41b0dbf1599296ba76343b942c39691a96a20ff382dad8cfc674889360d773e --ctx-size 32768 --batch-size 512 --n-gpu-layers 15 --threads 8 --parallel 1 --port 64270" time=2025-04-26T18:48:14.956-03:00 level=INFO source=sched.go:451 msg="loaded runners" count=1 time=2025-04-26T18:48:14.956-03:00 level=INFO source=server.go:580 msg="waiting for llama runner to start responding" time=2025-04-26T18:48:14.957-03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server error" time=2025-04-26T18:48:14.987-03:00 level=INFO source=runner.go:853 msg="starting go runner" ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 ROCm devices: Device 0: AMD Radeon RX 6800 XT, gfx1030 (0x1030), VMM: no, Wave Size: 32 load_backend: loaded ROCm backend from C:\Users\allan\AppData\Local\Programs\Ollama\lib\ollama\rocm\ggml-hip.dll load_backend: loaded CPU backend from C:\Users\allan\AppData\Local\Programs\Ollama\lib\ollama\ggml-cpu-haswell.dll time=2025-04-26T18:48:15.195-03:00 level=INFO source=ggml.go:109 msg=system CPU.0.SSE3=1 CPU.0.SSSE3=1 CPU.0.AVX=1 CPU.0.AVX2=1 CPU.0.F16C=1 CPU.0.FMA=1 CPU.0.BMI2=1 CPU.0.LLAMAFILE=1 CPU.1.LLAMAFILE=1 ROCm.0.NO_VMM=1 ROCm.0.NO_PEER_COPY=1 ROCm.0.PEER_MAX_BATCH_SIZE=128 compiler=cgo(clang) time=2025-04-26T18:48:15.196-03:00 level=INFO source=runner.go:913 msg="Server listening on 127.0.0.1:64270" time=2025-04-26T18:48:15.207-03:00 level=INFO source=server.go:614 msg="waiting for server to become available" status="llm server loading model" llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon RX 6800 XT) - 16226 MiB free llama_model_loader: loaded meta data with 42 key-value pairs and 377 tensors from C:\Users\allan\.ollama\models\blobs\sha256-c41b0dbf1599296ba76343b942c39691a96a20ff382dad8cfc674889360d773e (version GGUF V3 (latest)) llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output. llama_model_loader: - kv 0: general.architecture str = deepseek2 llama_model_loader: - kv 1: general.name str = DeepSeek-Coder-V2-Lite-Instruct llama_model_loader: - kv 2: deepseek2.block_count u32 = 27 llama_model_loader: - kv 3: deepseek2.context_length u32 = 163840 llama_model_loader: - kv 4: deepseek2.embedding_length u32 = 2048 llama_model_loader: - kv 5: deepseek2.feed_forward_length u32 = 10944 llama_model_loader: - kv 6: deepseek2.attention.head_count u32 = 16 llama_model_loader: - kv 7: deepseek2.attention.head_count_kv u32 = 16 llama_model_loader: - kv 8: deepseek2.rope.freq_base f32 = 10000.000000 llama_model_loader: - kv 9: deepseek2.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 10: deepseek2.expert_used_count u32 = 6 llama_model_loader: - kv 11: general.file_type u32 = 7 llama_model_loader: - kv 12: deepseek2.leading_dense_block_count u32 = 1 llama_model_loader: - kv 13: deepseek2.vocab_size u32 = 102400 llama_model_loader: - kv 14: deepseek2.attention.kv_lora_rank u32 = 512 llama_model_loader: - kv 15: deepseek2.attention.key_length u32 = 192 llama_model_loader: - kv 16: deepseek2.attention.value_length u32 = 128 llama_model_loader: - kv 17: deepseek2.expert_feed_forward_length u32 = 1408 llama_model_loader: - kv 18: deepseek2.expert_count u32 = 64 llama_model_loader: - kv 19: deepseek2.expert_shared_count u32 = 2 llama_model_loader: - kv 20: deepseek2.expert_weights_scale f32 = 1.000000 llama_model_loader: - kv 21: deepseek2.rope.dimension_count u32 = 64 llama_model_loader: - kv 22: deepseek2.rope.scaling.type str = yarn llama_model_loader: - kv 23: deepseek2.rope.scaling.factor f32 = 40.000000 llama_model_loader: - kv 24: deepseek2.rope.scaling.original_context_length u32 = 4096 llama_model_loader: - kv 25: deepseek2.rope.scaling.yarn_log_multiplier f32 = 0.070700 llama_model_loader: - kv 26: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 27: tokenizer.ggml.pre str = deepseek-llm llama_model_loader: - kv 28: tokenizer.ggml.tokens arr[str,102400] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 29: tokenizer.ggml.token_type arr[i32,102400] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 30: tokenizer.ggml.merges arr[str,99757] = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "h e... llama_model_loader: - kv 31: tokenizer.ggml.bos_token_id u32 = 100000 llama_model_loader: - kv 32: tokenizer.ggml.eos_token_id u32 = 100001 llama_model_loader: - kv 33: tokenizer.ggml.padding_token_id u32 = 100001 llama_model_loader: - kv 34: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 35: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 36: tokenizer.chat_template str = {% if not add_generation_prompt is de... llama_model_loader: - kv 37: general.quantization_version u32 = 2 llama_model_loader: - kv 38: quantize.imatrix.file str = /models/DeepSeek-Coder-V2-Lite-Instru... llama_model_loader: - kv 39: quantize.imatrix.dataset str = /training_data/calibration_datav3.txt llama_model_loader: - kv 40: quantize.imatrix.entries_count i32 = 293 llama_model_loader: - kv 41: quantize.imatrix.chunks_count i32 = 139 llama_model_loader: - type f32: 108 tensors llama_model_loader: - type f16: 2 tensors llama_model_loader: - type q8_0: 267 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q8_0 print_info: file size = 15.92 GiB (8.71 BPW) load: control-looking token: 100002 '<｜fim▁hole｜>' was not control-type; this is probably a bug in the model. its type will be overridden load: control-looking token: 100004 '<｜fim▁end｜>' was not control-type; this is probably a bug in the model. its type will be overridden load: control-looking token: 100003 '<｜fim▁begin｜>' was not control-type; this is probably a bug in the model. its type will be overridden load: special_eos_id is not in special_eog_ids - the tokenizer config may be incorrect load: special tokens cache size = 2400 load: token to piece cache size = 0.6661 MB print_info: arch = deepseek2 print_info: vocab_only = 0 print_info: n_ctx_train = 163840 print_info: n_embd = 2048 print_info: n_layer = 27 print_info: n_head = 16 print_info: n_head_kv = 16 print_info: n_rot = 64 print_info: n_swa = 0 print_info: n_swa_pattern = 1 print_info: n_embd_head_k = 192 print_info: n_embd_head_v = 128 print_info: n_gqa = 1 print_info: n_embd_k_gqa = 3072 print_info: n_embd_v_gqa = 2048 print_info: f_norm_eps = 0.0e+00 print_info: f_norm_rms_eps = 1.0e-06 print_info: f_clamp_kqv = 0.0e+00 print_info: f_max_alibi_bias = 0.0e+00 print_info: f_logit_scale = 0.0e+00 print_info: f_attn_scale = 0.0e+00 print_info: n_ff = 10944 print_info: n_expert = 64 print_info: n_expert_used = 6 print_info: causal attn = 1 print_info: pooling type = 0 print_info: rope type = 0 print_info: rope scaling = yarn print_info: freq_base_train = 10000.0 print_info: freq_scale_train = 0.025 print_info: n_ctx_orig_yarn = 4096 print_info: rope_finetuned = unknown print_info: ssm_d_conv = 0 print_info: ssm_d_inner = 0 print_info: ssm_d_state = 0 print_info: ssm_dt_rank = 0 print_info: ssm_dt_b_c_rms = 0 print_info: model type = 16B print_info: model params = 15.71 B print_info: general.name = DeepSeek-Coder-V2-Lite-Instruct print_info: n_layer_dense_lead = 1 print_info: n_lora_q = 0 print_info: n_lora_kv = 512 print_info: n_ff_exp = 1408 print_info: n_expert_shared = 2 print_info: expert_weights_scale = 1.0 print_info: expert_weights_norm = 0 print_info: expert_gating_func = softmax print_info: rope_yarn_log_mul = 0.0707 print_info: vocab type = BPE print_info: n_vocab = 102400 print_info: n_merges = 99757 print_info: BOS token = 100000 '<｜begin▁of▁sentence｜>' print_info: EOS token = 100001 '<｜end▁of▁sentence｜>' print_info: EOT token = 100001 '<｜end▁of▁sentence｜>' print_info: PAD token = 100001 '<｜end▁of▁sentence｜>' print_info: LF token = 185 'Ċ' print_info: FIM PRE token = 100003 '<｜fim▁begin｜>' print_info: FIM SUF token = 100002 '<｜fim▁hole｜>' print_info: FIM MID token = 100004 '<｜fim▁end｜>' print_info: EOG token = 100001 '<｜end▁of▁sentence｜>' print_info: max token length = 256 load_tensors: loading model tensors, this can take a while... (mmap = true) load_tensors: offloading 15 repeating layers to GPU load_tensors: offloaded 15/28 layers to GPU load_tensors: ROCm0 model buffer size = 8894.92 MiB load_tensors: CPU_Mapped model buffer size = 8623.01 MiB llama_context: constructing llama_context llama_context: n_seq_max = 1 llama_context: n_ctx = 32768 llama_context: n_ctx_per_seq = 32768 llama_context: n_batch = 512 llama_context: n_ubatch = 512 llama_context: causal_attn = 1 llama_context: flash_attn = 0 llama_context: freq_base = 10000.0 llama_context: freq_scale = 0.025 llama_context: n_ctx_per_seq (32768) < n_ctx_train (163840) -- the full capacity of the model will not be utilized llama_context: CPU output buffer size = 0.40 MiB init: kv_size = 32768, offload = 1, type_k = 'f16', type_v = 'f16', n_layer = 27, can_shift = 0 init: ROCm0 KV buffer size = 4800.00 MiB init: CPU KV buffer size = 3840.00 MiB llama_context: KV self size = 8640.00 MiB, K (f16): 5184.00 MiB, V (f16): 3456.00 MiB llama_context: ROCm0 compute buffer size = 1434.38 MiB llama_context: ROCm_Host compute buffer size = 74.01 MiB llama_context: graph nodes = 1951 llama_context: graph splits = 192 (with bs=512), 3 (with bs=1) time=2025-04-26T18:49:03.050-03:00 level=INFO source=server.go:619 msg="llama runner started in 48.09 seconds" [GIN] 2025/04/26 - 18:49:37 | 200 | 1m23s | 127.0.0.1 | POST "/api/chat" time=2025-04-26T18:49:38.086-03:00 level=WARN source=ggml.go:152 msg="key not found" key=general.alignment default=32 [GIN] 2025/04/26 - 18:50:41 | 200 | 1m3s | 127.0.0.1 | POST "/api/chat" ``` ### OS Windows ### GPU AMD ### CPU _No response_ ### Ollama version _No response_
GiteaMirror added the bug label 2026-05-04 15:37:40 -05:00
GiteaMirror commented 2026-05-04 15:37:45 -05:00
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@FlynnDowey commented on GitHub (Apr 28, 2025):

You will need to install ROCm v6.1 for GPU support on windows.

<!-- gh-comment-id:2836216403 --> @FlynnDowey commented on GitHub (Apr 28, 2025): You will need to install ROCm v6.1 for GPU support on windows.
GiteaMirror commented 2026-05-04 15:37:47 -05:00
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@rick-github commented on GitHub (May 12, 2025):

Is this still an issue?

<!-- gh-comment-id:2871454316 --> @rick-github commented on GitHub (May 12, 2025): Is this still an issue?
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Reference: github-starred/ollama#68910
Delete Branch "%!s()"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?