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Originally created by @yuval-ngtnuma on GitHub (Jun 26, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/11209
Originally assigned to: @dhiltgen on GitHub.
What is the issue?
I just upgraded ollama on my Windows 10 Pro (22H2, OS build 19045.5965) PC to 0.9.3. The PC has two NVidia 2080 Ti GPUs (driver version 560.94). I am not sure what version it was before, but I previously upgraded within the past two months.
Since the upgrade, I am unable to run any model. I get the error:
The most relevant log message looks like this one:
Relevant log output
OS
Windows
GPU
Nvidia
CPU
Intel
Ollama version
0.9.3
@yuval-ngtnuma commented on GitHub (Jun 26, 2025):
I can confirm after downgrading to 0.9.2, that the problem is indeed with 0.9.3, as 0.9.2 works fine.
@dhiltgen commented on GitHub (Jun 26, 2025):
This might be a dependency problem.
To test that theory, can you install the MSVC C++ runtime package and let us know if 0.9.3 starts working correctly?
@jpdr-apps commented on GitHub (Jun 26, 2025):
I installed the C++ libraries and the problem was solved. Moreover, I have 2 laptops, and the one which already had the libraries before didn't have this issue. Now both are runing Ollama as usual.
@dhiltgen commented on GitHub (Jun 26, 2025):
Sorry about that! We'll get this fixed in the next version. Until then, if anyone hits this, manually installing the C++ runtime will resolve the crash.
https://aka.ms/vs/17/release/vc_redist.x64.exe
@mayflyfy commented on GitHub (Jun 28, 2025):
I have the same problem,
win10 nvidia intel
@bit-yuyuyu commented on GitHub (Jun 30, 2025):
I have the same problem,Ubuntu 20.04, Nvidia A6000 * 4, intel
the log
6月 30 14:42:59 serer-A6000 ollama[3752607]: print_info: max token length = 256
6月 30 14:42:59 serer-A6000 ollama[3752607]: load_tensors: loading model tensors, this can take a while... (mmap = true)
6月 30 14:43:00 serer-A6000 ollama[3752607]: alloc_tensor_range: failed to initialize tensor output.weight
6月 30 14:43:00 serer-A6000 ollama[3752607]: llama_model_load: error loading model: unable to allocate CUDA0 buffer
6月 30 14:43:00 serer-A6000 ollama[3752607]: llama_model_load_from_file_impl: failed to load model
6月 30 14:43:00 serer-A6000 ollama[3752607]: panic: unable to load model: /usr/share/ollama/.ollama/models/blobs/sha256-a8cc1361f3145dc01f6d77c6c82c9116b9ffe3c97b34716fe20418455876c40e
6月 30 14:43:00 serer-A6000 ollama[3752607]: goroutine 257 [running]:
6月 30 14:43:00 serer-A6000 ollama[3752607]: github.com/ollama/ollama/runner/llamarunner.(*Server).loadModel(0xc0007ec360, {0x29, 0x0, 0x1, {0x0, 0x0, 0x0}, 0xc00078d690, 0x0}, {0x7ffe897f>6月 30 14:43:00 serer-A6000 ollama[3752607]: github.com/ollama/ollama/runner/llamarunner/runner.go:751 +0x395
6月 30 14:43:00 serer-A6000 ollama[3752607]: created by github.com/ollama/ollama/runner/llamarunner.Execute in goroutine 1
6月 30 14:43:00 serer-A6000 ollama[3752607]: github.com/ollama/ollama/runner/llamarunner/runner.go:848 +0xb57
6月 30 14:43:00 serer-A6000 ollama[3752607]: time=2025-06-30T14:43:00.569+08:00 level=ERROR source=server.go:464 msg="llama runner terminated" error="exit status 2"
6月 30 14:43:00 serer-A6000 ollama[3752607]: time=2025-06-30T14:43:00.597+08:00 level=ERROR source=sched.go:489 msg="error loading llama server" error="llama runner process has terminated:>6月 30 14:43:00 serer-A6000 ollama[3752607]: [GIN] 2025/06/30 - 14:43:00 | 500 | 3.184085189s | 127.0.0.1 | POST "/api/generate"
6月 30 14:43:05 serer-A6000 ollama[3752607]: time=2025-06-30T14:43:05.930+08:00 level=WARN source=sched.go:687 msg="gpu VRAM usage didn't recover within timeout" seconds=5.332562432 runner>6月 30 14:43:06 serer-A6000 ollama[3752607]: time=2025-06-30T14:43:06.270+08:00 level=WARN source=sched.go:687 msg="gpu VRAM usage didn't recover within timeout" seconds=5.67258538 runner.>6月 30 14:43:06 serer-A6000 ollama[3752607]: time=2025-06-30T14:43:06.609+08:00 level=WARN source=sched.go:687 msg="gpu VRAM usage didn't recover within timeout" seconds=6.011434446 runner>6月 30 14:44:19 serer-A6000 systemd[1]: Stopping Ollama Service...
6月 30 14:44:19 serer-A6000 systemd[1]: ollama.service: Succeeded.
6月 30 14:44:19 serer-A6000 systemd[1]: Stopped Ollama Service.
6月 30 14:45:31 serer-A6000 systemd[1]: Started Ollama Service.
6月 30 14:45:31 serer-A6000 ollama[3804822]: time=2025-06-30T14:45:31.989+08:00 level=INFO source=routes.go:1235 msg="server config" env="map[CUDA_VISIBLE_DEVICES:1,2,3 GPU_DEVICE_ORDINAL:>6月 30 14:45:31 serer-A6000 ollama[3804822]: time=2025-06-30T14:45:31.990+08:00 level=INFO source=images.go:476 msg="total blobs: 5"
6月 30 14:45:31 serer-A6000 ollama[3804822]: time=2025-06-30T14:45:31.991+08:00 level=INFO source=images.go:483 msg="total unused blobs removed: 0"
6月 30 14:45:31 serer-A6000 ollama[3804822]: time=2025-06-30T14:45:31.991+08:00 level=INFO source=routes.go:1288 msg="Listening on [::]:11434 (version 0.9.3)"
6月 30 14:45:31 serer-A6000 ollama[3804822]: time=2025-06-30T14:45:31.991+08:00 level=INFO source=gpu.go:217 msg="looking for compatible GPUs"
6月 30 14:45:32 serer-A6000 ollama[3804822]: time=2025-06-30T14:45:32.467+08:00 level=INFO source=types.go:130 msg="inference compute" id=GPU-e540b747-7f9d-2783-4c15-368667c9c829 library=c>lines 358247-358294/359381 100%
(base) serer@serer-A6000:~$ ollama run qwen3:14b
Error: llama runner process has terminated: error loading model: unable to allocate CUDA0 buffer
@wiskewu commented on GitHub (Jul 1, 2025):
it works. solved my problem.
@SDwarfs commented on GitHub (Jul 1, 2025):
This also fixed the issue for me on Windows 10 Pro, RTX 3060. Thank you.
@dhiltgen commented on GitHub (Jul 1, 2025):
Fixed in 0.9.4 - we now include the redistributable in the windows installer, and will conditionally install it if not detected on the system already.
@sunhy0316 commented on GitHub (Aug 25, 2025):
Is vc_redist unnecessary in the newest version with statically linked VC libraries? I canceled the vc_redist installation (no admin rights) during 0.11.6 setup, but the application works fine regardless.
@dhiltgen commented on GitHub (Aug 25, 2025):
We've reduced the dependency, but the ROCm libraries still depend on vc_redist.