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[GH-ISSUE #12908] ROCM Library not found, wrong location? - gfx1201 unsupported in current container image #34316
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opened 2026-04-22 17:45:47 -05:00 by GiteaMirror
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Originally created by @lu2 on GitHub (Nov 2, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/12908
Originally assigned to: @dhiltgen on GitHub.
What is the issue?
Using latest docker image of ollama:rocm with AMD Radeon RX 9070 XT
Getting following errors in the log, when model is loaded and talked to:
Looking in the container, this library exists, but on different location:
Should this be fixed in the image or maybe in ollama itself?
Relevant log output
OS
Docker
GPU
AMD
CPU
Intel
Ollama version
0.12.9
@dhiltgen commented on GitHub (Nov 5, 2025):
It looks like this is specific to gfx12 which now brings in a dependency on hipblaslt tensile files, which we do not currently bundle. We've fallen a bit behind on ROCm which complicates supporting the latest AMD GPUs. We're working to get Vulkan enabled soon which will provide coverage for a broad set of GPUs, and allow us to leapfrog to a much newer version of ROCm (likely based on TheRock) while still maintaining a broad set of supported GPUS between ROCm+Vulkan.
@andornaut commented on GitHub (Nov 6, 2025):
@dhiltgen
So, is this a regression? Do you know the last working version of Ollama (container image) for e.g. 9070xt?
@tmench23 commented on GitHub (Nov 17, 2025):
I currently am facing the same issue with the 9070 (non XT variant). Are there any known workarounds?
@xzxshmuner-boop commented on GitHub (Nov 19, 2025):
@dhiltgen
Are there any plans for when to support the latest AMD rocm
@NexGen-3D-Printing commented on GitHub (Nov 20, 2025):
I just hit this error with RX 9060 XT 16GB as well, I assume this is why I'm seeing underwhelming performance, as the same GPU under LMStudio is almost twice as responsive.
@dhiltgen commented on GitHub (Nov 21, 2025):
I have a draft PR to update a newer ROCm, but saw crashes on a few of our test systems which work fine on the current version of ROCm we're bundling, so we paused updating until we can get Vulkan enabled by default. Then Vulkan can provide a fall-back for any systems/GPUs where the newer ROCm becomes a regression. Ultimately I plan to update the PR with a ROCm v7 or potentially nightly build of TheRock.
@NexGen-3D-Printing commented on GitHub (Nov 21, 2025):
I just tried to switch to Vulkan, but unfortunately under TrueNAS Scale, Vulkan is not available for Ollama, logs say its disabled.
Standard image is CPU only, I'm not able to apply this under TrueNAS: "set OLLAMA_VULKAN=1"
@MorrisLu-Taipei commented on GitHub (Dec 14, 2025):
same issue, no any workaround so far.
@hopperath commented on GitHub (Jan 7, 2026):
Similiar issue with 9060XT 16gb as well, rocm 7.1.1. If I link the file from the rocm directory the "no such file" message goes away, but still fails with
rocblaslt error: Could not load /usr/local/lib/ollama/rocm/hipblaslt/library/TensileLibrary_lazy_gfx1200.dat
hipBLASLt error: Heuristic Fetch Failed!
@androiddrew commented on GitHub (Feb 5, 2026):
@lu2 I have a fork https://github.com/androiddrew/ollama/tree/drew/rocm7p2 where I built Ollama with ROCm 7.2. I believe I resolved the errors you were seeing:
I built a docker image to test with too https://hub.docker.com/repository/docker/androiddrew/ollama/tags/0.15.4-rocm-7.2/sha256-5de6c0238bc99642b54af76abcfcf1506cbf4c52e6a1ffe727ef0f8bfaeacff8
Let me know if it works for you.
Though will show that there are no tuned kernels for the gfx1201 only fallback kernels. I am only seeing 18 TPS for https://huggingface.co/unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF/blob/main/Devstral-Small-2-24B-Instruct-2512-UD-Q8_K_XL.gguf. That is a dense model but I would have expected some better performance than that.
@dhiltgen please take a look at my fork, if it's up to expectations I could create a PR.
@androiddrew commented on GitHub (Feb 5, 2026):
Just compared LM Studio and my Ollama solution. Same 33TPS effectively for the 4 bit Devstral 2 small 24B model on my gfx1201. So...yeah I guess the next step is figuring out how to squeeze more out of this now with maybe Tensile finetuning.
I am trying to figure out how these Tensile libraries are produced for the rocm/dev-almalinux-8:7.2-complete image that was used for those rocm kernels.
@lu2 commented on GitHub (Feb 5, 2026):
Thanks @androiddrew . I just tried your docker image androiddrew/ollama:0.15.4-rocm-7.2
The error message is indeed gone, but performance wise, it is same like official ollama/ollama:rocm.
I have to let more clever people to compare the results:
androiddrew/ollama:0.15.4-rocm-7.2 results:
ollama/ollama:rocm (675519d3d134) 3 days ago version results:
@androiddrew commented on GitHub (Feb 5, 2026):
@lu2
the Devstral2 Small model is pretty beefy and will exceed the 30 Gib of vram unless you use low context len..
OLLAMA_CONTEXT_LENGTHset to something low like 8192 should put the whole model on your gpu.The missing 2 GiB on these cards is apparently because of ecc. I hear you can turn it off to get the full 32 GiB on your card, but then you run some different risks.
@dhiltgen commented on GitHub (Mar 11, 2026):
Release 0.17.8 updates Linux to ROCm v7 which covers support for this GPU. Please give the RC a try and let us know if you run into any problems.
@depuhitv commented on GitHub (Mar 28, 2026):
This error still shows up in the latest docker ollama/ollama:rocm image on 0.19.0-rc0. e6777885093e