The `HSA_OVERRIDE_GFX_VERSION` variable can be used in ROCm to override an unsupported target architecture with a similar but supported target architecture.
This does not and has never worked on Windows. I think the clarification could avoid driving Windows people towards this solution that does not work.
* ggml-zendnn : add MUL_MAT_ID op support for MoE models
- Add MUL_MAT_ID op acceleration for Mixture-of-Experts models
- MUL_MAT_ID op fallback to CPU backend if total experts > 32
- Point ZenDNN lib to latest bits ZenDNN-2026-WW13
* ggml-zendnn : add braces to sgemm failure condition for consistency
Co-authored-by: Aaron Teo <taronaeo@gmail.com>
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Co-authored-by: Aaron Teo <taronaeo@gmail.com>
* seems to work
* fix case with new line
Co-authored-by: sayap <sokann@gmail.com>
* gemma 4: fix pre tok regex
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: sayap <sokann@gmail.com>
Reuse the buffer for the ggml context which is used for creating the
compute graph on the server side. This partially addresses a memory leak
created by the CUDA backend due to using buffer addresses as cache
keys.
ref: #21265
ref: #20315
* ci : add AMD CPU label to PR labeler
Add automatic labeling for PRs that modify AMD CPU (ZenDNN) backend files
* ci : rename label AMD CPU to AMD ZenDNN in labeler config
Co-authored-by: Aaron Teo <taronaeo@gmail.com>
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Co-authored-by: Aaron Teo <taronaeo@gmail.com>
Bump ROCm version on Linux from 7.2 to 7.2.1
Add gfx1102 target
Delete LLVM workaround since ROCm 7.2.1 has fix for ROCm 7.2 perf regression https://github.com/ROCm/rocm-systems/issues/2865
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Add unit test coverage for llama_tensor_get_type
* Fix merge conflicts, add more schemas
* clang formatter changes
* Trailing whitespace
* Update name
* Start rebase
* Updating files with upstream changes prior to rebase
* Changes needed from rebase
* Update attn_qkv schema, change throw behaviour
* Fix merge conflicts
* White space
* Update with latest changes to state counters
* Revert accidental personal CLAUDE.md changes
* Change quotation mark
* Reuse metadata.name since we have it
* Move test-only stuff out of llama-quant.cpp
* Hide the regex functionality back in llama-quant.cpp, use a unique pointer to a new struct 'compiled_tensor_type_patterns' which contains the patterns
* cont : inital deslop guidelines
* Cleanup based on review comments
* Continue cleanup
* Small cleanup
* Manually set proper ordering of tensors, mostly applies to gemma
* Formatting
* Update tests/test-quant-type-selection.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Fix merge conflicts
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* tests: allow exporting graph ops from HF file without downloading weights
* use unique_ptr for llama_context in HF metadata case
* fix missing non-required tensors falling back to type f32
* use unique pointers where possible
* use no_alloc instead of fixing f32 fallback
* fix missing space
* Relax prefill parser to allow space.
* Move changes from prefix() to parser generation
* Only allow spaces if we're not having a pure content parser next
* chat : add Granite 4.0 chat template with correct tool_call role mapping
Introduce `LLM_CHAT_TEMPLATE_GRANITE_4_0` alongside the existing Granite
3.x template (renamed `LLM_CHAT_TEMPLATE_GRANITE_3_X`).
The Granite 4.0 Jinja template uses `<tool_call>` XML tags and maps the
`assistant_tool_call` role to `<|start_of_role|>assistant<|end_of_role|><|tool_call|>`.
Without a matching C++ handler, the fallback path emits the literal role
`assistant_tool_call` which the model does not recognize, breaking tool
calling when `--jinja` is not used.
Changes:
- Rename `LLM_CHAT_TEMPLATE_GRANITE` to `LLM_CHAT_TEMPLATE_GRANITE_3_X`
(preserves existing 3.x behavior unchanged)
- Add `LLM_CHAT_TEMPLATE_GRANITE_4_0` enum, map entry, and handler
- Detection: `<|start_of_role|>` + (`<tool_call>` or `<tools>`) → 4.0,
otherwise → 3.x
- Add production Granite 4.0 Jinja template
- Add tests for both 3.x and 4.0 template paths (C++ and Jinja)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Code review: follow standard format and use common logic in test-chat-template.cpp
* Rename custom_conversation variable for extra_conversation to give it a more meaningful name
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* hexagon : add cumsum op support
* hexagon: enable dma for cumsum op
* Fix line-ending
---------
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
* fix: Bypass API Key validation for static bundle assets
* refactor: All bypassed routes in `public_endpoints`
* test: Update static assets API Key test
* kleidiai: add cpu feature detection to CI run script
Signed-off-by: Martin Klacer <martin.klacer@arm.com>
Change-Id: I663adc3a7691a98e7dac5488962c13cc344f034a
* kleidiai: revert unrelated requirements change
Signed-off-by: Martin Klacer <martin.klacer@arm.com>
* kleidiai: removed cpu feature detection from CI run script
* As per the maintainers' suggestion, removed cpu feature detection
from CI run script as CMake handles it already
Signed-off-by: Martin Klacer <martin.klacer@arm.com>
---------
Signed-off-by: Martin Klacer <martin.klacer@arm.com>
* Introduced NVFP4 generic MMQ kernel
* Added extra FP8 guard, hope to solve ci HIP failure
* Rename tiles and use HIP_FP8_AVAILABLE
* Removed remaning FP8 straggler and added const int
* Const
* Removed DECL_MMQ_CASE artifact
* Removed newline
* Removed space after else
* Changed HIP FP8 NVFP4 conversion gate
* Added new line to bottom of mmq.cu 270
* Removed extra spaces
* Removed single space in front of else on line 814
* Added NVFP4 to generate cu script so HIP can see it, further tightened logic
* Include generated mmq-instance-nvfp4.cu
* Added NVFP4 mmq to HIP Check ignore list
* Update ggml/src/ggml-cuda/mmq.cuh
Changed to Q3_K tile to read MMQ_MMA_TILE_X_K_NVFP4
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Update ggml/src/ggml-cuda/mmq.cuh
Changed to Q3_K tile to read MMQ_MMA_TILE_X_K_NVFP4 in tile assert
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Update ggml/src/ggml-cuda/mmq.cuh
Added function name ending for end if
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* Added function names to closing endif
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
The hybrid memory paths (`llama-memory-hybrid.cpp` and
`llama-memory-hybrid-iswa.cpp`) always used sequential equal split,
ignoring the unified KV cache flag. This caused hellaswag, winogrande,
and multiple-choice evaluations to fail on hybrid models (models with
both attention and recurrent/SSM layers, such as Qwen3.5-35B-A3B) with:
split_equal: sequential split is not supported when there are
coupled sequences in the input batch (you may need to use the
-kvu flag)
PR #19954 fixed this for `llama-kv-cache-iswa.cpp` by automatically
enabling unified KV mode and setting n_parallel >= 4 for multi-choice
eval tasks. However, the hybrid memory paths were not updated.
This commit mirrors the iswa fix: use non-sequential split when KV
cache is unified (n_stream == 1), which is automatically set by
llama-perplexity for hellaswag/winogrande/multiple-choice since #19954.
Tested on Qwen3.5-35B-A3B (hybrid attention+SSM MoE model):
- HellaSwag: 83.0% (400 tasks)
- Winogrande: 74.5% (400 tasks)
- MMLU: 41.2%
- ARC-Challenge: 56.2%
- TruthfulQA: 37.7%
All previously failed with llama_decode() error.
Piotr Wilkin
M1DNYT3
jeromew
Sigbjørn Skjæret
Aaron Teo
uvos
Tillerino
Vishal Singh
Radoslav Gerganov
Georgi Gerganov
Slobodan Josic
Bartowski
Zheyuan Chen
Ruben Ortlam
Xuan-Son Nguyen
Aldehir Rojas
Jesus Talavera
Roger Chen
Neo Zhang
Todor Boinovski
lhez
Aleksander Grygier
Johannes Gäßler
Martin Klacer
Nikhil Jain
Aparna M P
Jonathan
Michael Wand
Ettore Di Giacinto