* ggml: backend-agnostic tensor parallelism
* support for GPT-OSS, Qwen 3 MoE
* partial Vulkan fix
* add support for 4/8 GPUs
* unconditional peer access
* re-use buffers + ggml contexts
* fix output pattern
* NCCL support
* GGML: HIP: add RCCL support
* Remove shfl and AllReduce from backend interface
* move allocation workaround out of ggml-alloc.c
* 2d tensor set/get support
* Fix the seg fault without NCCL
* Apply suggestion from JohannesGaessler
* support for tensor dims % n_devs != 0
* fix view_offs scaling
* arbitrary num. of GPUs/tensor split
* fix compilation
* better granularity estimate
* Support device-specific host buffer types if all underlying backends expose the same type. This allows using pinned memory instead of pageable memory for CUDA.
Fix compilation errors.
* partial Qwen 3 Next support
* Fix qwen3 30b (#8)
* Fix crash with Qwen-30B-A3B Q4_0
Qwen-30B-A3B Q4_0 has an intermediate dimension of 768. Using a granularity of 256 forces an uneven split between GPUs, which is not supported by the current implementation.
* Decide block size based on tensor quantization type
* Fix crashes due to KV cache serialization (#9)
KV cache serialization requires non-zero offsets on the tensor. Add support in the meta backend to set/get a tensor with a non-zero offset.
* metal : fix build (#7)
* static memory allocations, fix usage count
* fix tensor granularity
* more even memory distribution
* use BF16 for allreduce
* rebase fixup
* better error message for unsupported architectures
* Fix device mismatch during scatter of allReduce. (#11)
There is a mismatch between the dst buffer device and the backend device, causing the use of sync copies
* Enable the previous allreduce implementation. It is better in both perf and stability (#12)
* delay AllReduce for Moe for less I/O
* build : clean-up compile warnings
* backend : move most of the meta backend API to ggml-backend-impl.h
* cont : hide unused public API in the implementation
* llama : use llama_device + remove ggml_backend_dev_is_meta()
* ggml-backend : remove unused alloc include
* minor : remove regex include
* ggml : introduce ggml-ext.h for staging new APIs
* rebase fixup
* fix tests
* llama : more robust logic for determining Meta devices (#16)
* llama : more robust logic for determining Meta devices
* cont : fix devs size check
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* cont : fix log type
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* disable roundtrip for meta backend
* fix arch selection
* Qwen 3.5 support
* fix Gemma 4 MoE
* fix OpenVino, SYCL
* fix test-llama-archs for CPU-only builds
* Fix Qwen 3.5 MoE
* disable meta backend tests for WebGPU
* tests : filter CPU-based devices from the Meta backend tests (#17)
* meta : formatting, naming, indentation (#18)
* formatting : llama-model.cpp
* formatting : ggml-ext.h
* formatting : ggml-backend-meta.cpp
* meta : add TODO
* add documentation
* better error messages
* fix GPT-OSS
---------
Co-authored-by: Carl Philipp Klemm <carl@uvos.xyz>
Co-authored-by: Gaurav Garg <gaugarg@nvidia.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* gemma : reduce graph splits by keeping per-layer ops in the input layer
* gemma : put the per-layer proj in the first layer
* cont : move the projection before the layer loop
* unicode : add custom Qwen2 regex handler to fix segfault on long input
std::regex uses recursive backtracking internally, which causes a stack
overflow (segfault) when tokenizing long sequences of repeated characters
(e.g. 43K 'A's). The Qwen2 tokenizer regex differs from Llama3 only in
the digit pattern (\p{N} vs \p{N}{1,3}), so it was falling through to
the std::regex fallback path instead of using a custom handler.
Add unicode_regex_split_custom_qwen2() following the established pattern
used by gpt2, llama3, kimi_k2, and afmoe custom handlers.
Closes: https://github.com/ggml-org/llama.cpp/issues/21113
* cont : remove TODO comment
* cont : update comment to reflect original regex
* use the correct regex in the comment this time... [no ci]
---------
Co-authored-by: Aldehir Rojas <hello@alde.dev>
* 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>
* 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>
* 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>
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.
* Refactor llama_model_quantize_params to expose a pure C interface
* Restore comment and cleanup struct def
* Code review refactoring
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Code review refactoring
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* mtmd: llama.cpp DeepSeekOCR support
init commit
* loading sam tensors
* mtmd: fix vision model processing
* deepseek-ocr clip-vit model impl
* mtmd: add DeepSeek-OCR LM support with standard attention
* mtmd: successfully runs DeepSeek-OCR LM in llama-cli
* mtmd: Fix RoPE type for DeepSeek-OCR LM.
* loading LM
testing Vision model loading
* sam warmup working
* sam erroneous return corrected
* clip-vit: corrected cls_embd concat
* clip-vit: model convert qkv_proj split
* corrected combining of image encoders' results
* fix: update callback for ffn_moe_weighted and add callback for attn_out in deepseek2 model
* concat image_newline and image_seperator tokens
* visual_model warmup (technically) works
* window partitioning using standard ggml ops
* sam implementation without using CPU only ops
* clip: fixed warnings
* Merge branch 'sf/deepseek-ocr' of github.com:sfallah/llama.cpp into sf/deepseek-ocr
* mtmd: fix get_rel_pos
* mtmd: fixed the wrong scaler for get_rel_pos
* image encoding technically works but the output can't be checked singe image decoding fails
* mtmd: minor changed
* mtmd: add native resolution support
* - image encoding debugged
- issues fixed mainly related wrong config like n_patches etc.
- configs need to be corrected in the converter
* mtmd: correct token order
* - dynamic resizing
- changes are concerning PR https://github.com/sfallah/llama.cpp/pull/4
* mtmd: quick fix token order
* mtmd: fix danling pointer
* mtmd: SAM numerically works
* mtmd: debug CLIP-L (vit_pre_ln)
* mtmd: debug CLIP-L & first working DeepSeek-OCR model
* mtmd : add --dsocr-mode CLI argument for DeepSeek-OCR resolution control & all native resolution modes work
* mtmd: simplify SAM patch embedding
* mtmd: adapt Pillow image resizing function
* mtmd: simplify DeepSeek-OCR dynamic resolution preprocessing
* mtmd: remove --dsocr-mode argument
* mtmd: refactor code & remove unused helper functions
* mtmd: fix tensor names for image newlines and view separator
* clean up
* reverting automatically removed spaces
* reverting automatically removed spaces
* mtmd: fixed bad ocr check in Deepseek2 (LM)
* mtmd: support combined QKV projection in buid_vit
* using common build_attn in sam
* corrected code-branch when flash-attn disabled
enabling usage of --flash-attn option
* mtmd: minor fix
* minor formatting and style
* fixed flake8 lint issues
* minor editorconfig-check fixes
* minor editorconfig-check fixes
* mtmd: simplify get_rel_pos
* mtmd: make sam hparams configurable
* mtmd: add detailed comments for resize_bicubic_pillow
* mtmd: fixed wrong input setting
* mtmd: convert model in FP16
* mtmd: minor fix
* mtmd: remove tweak to llama-mtmd-cli & deepseek-ocr template
* fix: test-1.jpg ORC issue with small (640) resolution
setting min-resolution base (1024) max large (1280) for dynamic-resolution
* minor: editconfig-check fix
* merge with changes from https://github.com/ggml-org/llama.cpp/pull/17909
added new opt to tests.sh to disable flash-attn
* minor: editconfig-check fix
* testing deepseek-ocr
quick and dirty test script comparing results of Qwen2.5-VL vs DeepSeek-OCR
* quick and (potential) dirty merge with https://github.com/ggml-org/llama.cpp/pull/17909
* refactoring, one single builder function and static helpers
* added deepseek-ocr test to tests.sh
* minor formatting fixes
* check with fixed expected resutls
* minor formatting
* editorconfig-check fix
* merge with changes from https://github.com/ggml-org/llama.cpp/pull/18042
* minor
- added GLM-4.6V to big tests
- added missing deps for python test
* convert: minor fix
* mtmd: format code
* convert: quick fix
* convert: quick fix
* minor python formatting
* fixed merge build issue
* merge resolved
- fixed issues in convert
- tested several deepseek models
* minor fix
* minor
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* - removed clip_is_deepseekocr
- removed redundant RESIZE_ALGO_BICUBIC_PILLOW resize-algo
- simplified image-preprocessing
- removed/simplified debug functions
* - cleaning commented out code
* fixing instabilities issues reintroducing resize_bicubic_pillow
* - use f16 model for deepseek-ocr test
- ignore llama-arch test for deepseek-ocr
* rename fc_w --> mm_fc_w
* add links to OCR discussion
* cleaner loading code
* add missing .weight to some tensors
* add default jinja template (to be used by server)
* move test model to ggml-org
* rolling back upscale change
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
---------
Co-authored-by: bluebread <hotbread70127@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
* grammar: add test case for nullable symbol loop
Reproduce stack overflow (or OOM) with ( [x]* )* found while adding
GBNF support to ripgrep-edit.
llama-server reproducer:
curl \
-X POST \
-d '{
"messages": [{ "role": "user", "content": "write yes" }],
"grammar": "root ::= ( [x]* )*"
}' \
-H "Content-Type: application/json" \
http://localhost:8811/v1/chat/completions
* grammar: prevent stack overflow with nullable symbol loop
Fix a potential stack overflow in llama_grammar_advance_stack that
could occur when processing grammars with nullable symbols that lead
to infinite derivations of empty strings. The fix introduces cycle
detection by tracking visited stacks to prevent infinite recursion.
rg-edit regexp: llama_grammar_advance_stack
rg-edit extra-args: -A20
rg-edit directive: """Rewrite: fix the following segfault:
[..]
⚫ Testing segfault. Grammar:
root ::= ( [x]* )*
root ::= ( [x]* )*
Segmentation fault build/bin/test-grammar-integration"""
gptel-context:
(("~/llama.cpp/src/llama-grammar.cpp")
("~/llama.cpp/tests/test-grammar-integration.cpp")
("~/llama.cpp/grammars/./list.gbnf")
("~/llama.cpp/grammars/./json_arr.gbnf")
("~/llama.cpp/grammars/./json.gbnf")
("~/llama.cpp/grammars/./japanese.gbnf")
("~/llama.cpp/grammars/./english.gbnf")
("~/llama.cpp/grammars/./chess.gbnf")
("~/llama.cpp/grammars/./c.gbnf")
("~/llama.cpp/grammars/./arithmetic.gbnf")
("~/llama.cpp/grammars/./README.md"))
* grammar: convert recursive llama_grammar_advance_stack to iterative
This change converts the function to an iterative approach using
explicit stacks, which prevents deep recursion and eliminates the risk
of stack overflow.
rg-edit regexp: llama_grammar_advance_stack
rg-edit extra-args: -A30
rg-edit directive: """Rewrite: fix the following segfault:
[..]
⚫ Testing segfault. Grammar:
root ::= ( [x]* )*
root ::= ( [x]* )*
Segmentation fault build/bin/test-grammar-integration
convert from recursive to interactive"""
gptel-context:
(("~/llama.cpp/src/llama-grammar.cpp")
("~/llama.cpp/tests/test-grammar-integration.cpp")
("~/llama.cpp/grammars/./list.gbnf")
("~/llama.cpp/grammars/./json_arr.gbnf")
("~/llama.cpp/grammars/./json.gbnf")
("~/llama.cpp/grammars/./japanese.gbnf")
("~/llama.cpp/grammars/./english.gbnf")
("~/llama.cpp/grammars/./chess.gbnf")
("~/llama.cpp/grammars/./c.gbnf")
("~/llama.cpp/grammars/./arithmetic.gbnf")
("~/llama.cpp/grammars/./README.md"))
v2: Added a `std::set` to perform tree-based lookups with O(N log N)
complexity. Testing with a parallel run of `test-grammar-integration`
shows a double-digit percentage increase in runtime. An
`unordered_set` with O(1) hashing was also evaluated, but the overhead
of constructing hash keys from pointers made it significantly slower
than the rbtree implementation that only requires an ordering
operator. The performance regression in the test suite appears
justified by the overall reduction in algorithmic complexity.
Co-developed-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>
* grammar: add test case for hang in repetition grammar processing
This commit adds a new test case to the grammar integration tests that
specifically targets a hang scenario in the repetition grammar parser
found while adding GBNF support to ripgrep-edit.
llama-server reproducer:
curl \
-X POST \
-d '{
"messages": [{ "role": "user", "content": "write yes" }],
"grammar": "root ::= (([^x]*){0,99}){0,99}"
}' \
-H "Content-Type: application/json" \
http://localhost:8811/v1/chat/completions
* grammar: add repetition threshold check
The change introduces a maximum repetition threshold to avoid
excessive rule expansion during grammar parsing. When parsing
repetition patterns like {m,n}, the parser now calculates the
potential number of rules that would be generated and throws an error
if the product of previous rules and new rules exceeds the threshold.
A test case was added to verify the threshold is properly enforced for
deeply nested repetition patterns that would otherwise cause hangs.
The MEAN/CLS/LAST pooling paths in encode() and decode() used
n_embd_inp() (16384 for qwen3vl with deepstack) to read from the
pooled embedding tensor, which only has n_embd_out() (4096) floats
per sequence. This caused a tensor read out of bounds assertion.
Fixes embedding mode for Qwen3-VL-Embedding models.
* Check granite hybriid expert count to set type as LLM_TYPE_7B_A1B or LLM_TYPE_1B
* Use feed fwd dim instead of num of experts
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* context: zero output buffer on allocation
Address GHSA-wqq9-25mr-rw76.
The logits output buffer allocated in output_reserve() uses
posix_memalign(), which does not zero memory. The buffer is only
written during decode when needs_raw_logits() returns true. When
backend samplers cover all output sequences, needs_raw_logits()
returns false and the buffer is never written, but
llama_get_logits() still returns a pointer to it, exposing stale
heap content.
Zero the buffer after allocation to prevent information disclosure
through the public logits API.
Found-by: Pwno
* Update src/llama-context.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Add control vector functions to qwen3.5 and qwen-next models
* Add missing cvec compatibility to the rest of the models
* Adjust comments and formatting
* cleanup
* whitespace
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
MoonRide303
Johannes Gäßler
Xuan-Son Nguyen
Piotr Wilkin (ilintar)
Aldehir Rojas
Erik Scholz
Georgi Gerganov
Son H. Nguyen
Pasha Khosravi
anchortense
Richard Davison
SamareshSingh
Aman Gupta
Bartowski
Jesus Talavera
Ettore Di Giacinto
Ed Addario
lainon1
Sigbjørn Skjæret
Saba Fallah
Michael Wand
Dowon
Andrea Arcangeli
Tom Hillbrunner
Victor Villar
Ruikai Peng
Michael Grau
Pop Flamingo
Andreas Obersteiner