* common: skip reasoning budget sampler when no budget is requested
After I added thinking_start_tag / thinking_end_tag for gemma4 in #21697, the reasoning budget sampler gets unconditionally created even when no budget is configured (the default -1). The same applies to kimi_k2, lfm2, lfm2_5, and ministral_3 which also set these tags. The budget gets converted to INT_MAX, so the sampler never actually forces any tokens but still runs per-token checks (start tag matching in IDLE state, token-to-piece conversion + UTF-8 checks in COUNTING state).
More importantly, the mere existence of the sampler (non-null rbudget) disables backend sampling. Backend sampling lets the GPU select tokens directly, avoiding a full logits transfer from GPU to CPU every token. This could explain the 30% speed regression reported in #21784 (98 t/s to 70 t/s on Vulkan).
So I added a reasoning_budget_tokens >= 0 check to the sampler creation condition. When the budget is unlimited, the sampler is not created, backend sampling stays enabled, and no per-token overhead is added. When a budget is explicitly set (0, 128, 1024, etc.), the sampler is created and works as before.
* common: preserve rbudget when grammar is lazy
Following up on the review feedback on #21870: keep the reasoning budget sampler when grammar_lazy is true, so the thinking-block grammar suppression from #20970 still works when tools are in use. This way, we only skip the sampler when both no budget is set AND grammar is not lazy.
* webui: add setting for first-line chat titles
Add an opt-in setting (`titleGenerationUseFirstLine`) to use the first
non-empty line of a prompt as the generated conversation title.
Previously, the complete multi-line prompt was being used, which created
long titles for complex queries. Coupled with
"Ask for confirmation before changing conversation title", the dialog
would overflow.
* Update tools/server/webui/src/lib/utils/text.ts
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* Update tools/server/webui/src/lib/utils/text.ts
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* webui: Run build to update the bundle
As requested in:
https://github.com/ggml-org/llama.cpp/pull/21797#pullrequestreview-4094935065
* webui: Fix missing import for NEWLINE_SEPARATOR
---------
Co-authored-by: Aleksander Grygier <aleksander.grygier@gmail.com>
* Add MCP Connection diagnostics and CORS hint to web-ui
* tidy up test
* webui: Refactor and improve MCP diagnostic logging
---------
Co-authored-by: evalstate <1936278+evalstate@users.noreply.github.com>
* add qwen3a
* wip
* vision ok
* no more deepstack for audio
* convert ASR model ok
* qwen3 asr working
* Apply suggestions from code review
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* nits
* Apply suggestions from code review
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* fix bad merge
* fix multi inheritance
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* mtmd : add MERaLiON-2 multimodal audio support
Adds support for A*STAR's MERaLiON-2 audio-language model (3B and 10B)
to the multimodal framework.
Architecture:
- Whisper large-v2 encoder for audio feature extraction
- Gated MLP adaptor: ln_speech -> frame stack (x15) -> Linear+SiLU -> GLU -> out_proj
- Gemma2 3B / 27B decoder
The mmproj GGUF is generated via convert_hf_to_gguf.py --mmproj on the full
MERaLiON-2 model directory (architecture: MERaLiON2ForConditionalGeneration).
The decoder is converted separately as a standard Gemma2 model after stripping
the text_decoder. weight prefix.
New projector type: PROJECTOR_TYPE_MERALION
Supports tasks: speech transcription (EN/ZH/MS/TA), translation, spoken QA.
Model: https://huggingface.co/MERaLiON/MERaLiON-2-3Bhttps://huggingface.co/MERaLiON/MERaLiON-2-10B
* simplify comments in meralion adaptor
* meralion: use format_tensor_name, ascii arrows in comments
* hexagon: introduce op request batching and rewrite buffer managment
The host now prepares batches of requests and dispatches them via a single dspqueue message.
Buffers are mapped explicitly by NPU while processing batches.
* hex-dma: disable l2 bypass since to work around new issue due to no flushes between Ops
* hex-utils: add explicit l2flush and l2clear helpers
* hex-opreq: use fine-grain per tensor l2 management
* hex-opreq: avoid redundant invalidates for tensors we already flushed
* hex-opreq: update debug messages
* htp-opreq: reuse ops_context
* hex-opreq: do not flush or invalidate cache lines beyond buffer boundry
* hex-opreq: fix errors in log message
* Revert "hex-opreq: do not flush or invalidate cache lines beyond buffer boundry"
This reverts commit 8b7f0a55a750a6430ce4eb1874c7feb3d720056d.
* hexagon: limit l2 flushes to 1MB which covers l2 cache
* hex-opreq: limit cache flush to 4MB
Looks like 4MB cont. vitual space should cover the 1MB cache.
* hexagon: drop cache flush size to 2MB
* hex-opreq: start reworking opreq packing
* hex-opreq: introduce new way of packing opbatch where tensors are stored separately
* hex-opreq: add a simple fastrpc call to force unmap all buffers
* hex-l2flush: somehow 2MB does not seem robust, also cleanup step size to use line-size
* hex-opreq: bump opreq batch size to 256
* hex-mm: place src1 spad at the top of vtcm for easy reuse
* hex-ops: introduce internal types and disable src1 reuse for now
Nothing new just formalizing the repack / qyn.quant types we've been using.
* htp-opreq: use tensor pointers instead of copies
* hex-opreq: introduce more robust way for tracking vtcm/spad reuse
This removes the SKIP_QUANTIZE flag that became fragile with the addition of HMX and other ops.
* hex-cumsum: fix error post opreq merge
* hex-opreq: move request batch handling into the session
Prepping everything for using dspqueue buffers and doing that inside the session is much cleaner.
* hex-mm: yet another fix for src1 reuse when we're mixing hmx/hvx
* hex-bufs: introduce pinned mmapings and use non-pinned ones for model buffers
* hex-buf: add support for allocating shared/pinned buffer for opreqs
* hex-opbatch: make opbatches configurable
* hex-naming: better name for ggml_hexagon_shared_buffer
* hex-naming: add session->c_name() helper
* hex-opbatch: start using shm but still copy for now
* hex-opbatch: use shared buffer for packing opbatch
* hex-opbatch: beter naming for opbatch related classes and code
* hex-opbatch: reuse batched tensors with same data/dims/strides
* hex-opbatch: update logging
* hex-opbatch: add support for vmem limit for op batching
* hex-opbatch: update htp side to properly support dynamic mmap/unmap
* hex-opbatch: add OB and OQ params for run-completion script and fix the asserts in batch processing
* hex-opbatch: fixed src1 handling in act ops
* hex-act: fix empty src1 handling in swiglu and friends
Simplify preamble macro while at it
* hex-mm: minor fix vtcm and dma handling in matmul
cleaning up some left-overs from merges
* hex-opbatch: allocate extra 1KB for dspqueue overhead
* hexagon: fix softmax for non-aligned tensors and cleanup vtcm alloc
* hex-mm: properly handle hmx_disabled flag
* hex-ops: update comments
* hex-ops: add debug output for get/set-rows
* hex-mmap: optimize un/mapping of buffers
* hex-opreq: global cache flush and invalidate beyond 128KB threshold
* hex-ops: add super simple opfilter regex for debugging
If an Op matches the regex hex backend will reject it.
* hex-opbatch: wireup newer ops missed in merge and update main switch to detect this in future
* hexagon: improved vtcm acquision to remove inter-op overhead
Fully compatible with QNN-HTP coex
* hex-mm: fixed hvx fallback path
* hex-mm: lower the vmem threshold a bit further to ~3GB
* hexagon: update debug & error logs
This also fixes an issue with newer llvm merging repack and non-repack
functions. We use those pointer to distinguish between buffer types.
* hexagon: move ops context into main context
Just a cleanup. We don't need separate contexts at this point.
* hex-opbatch: cleanup naming and headers for opbatch and related descriptors
* hex-fa: it's now better to enable FA during TG to reduce graph splits
* hexagon: remove GGML_HEXAGON_EXPERIMENTAL env var
It's no longer useful. Please use more flexible GGML_HEXAGON_OPFILTER to disable Ops
if needed for debugging or validation.
* hexagon: fixed editorconfig check
* Update ggml/src/ggml-hexagon/ggml-hexagon.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
---------
Co-authored-by: Trivikram Reddy <tamarnat@qti.qualcomm.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* ggml(webgpu): fix the busy-polls in Emscripten in the waitAny after #20618, and remove the busy webgpu log
* Merge with upstream
* Fix GET_ROWS packed integer NaN when using f16 as memory buffer in shader quants
* Update Unary wgsl EXP and EXPM1 for f16 stability
* Fix GET_ROWS IQ4_XS strcut for NaN f16 canonicalization
* Fix numerical percision for unary sqrt when working with f16
* Fix NaN canonicalization for packed integers using f16
* Update err threshold for binary div ops when using f16
* backend: Keep one Dawn/WebGPU instance alive for the lifetime of the static backend
* clean: uncomment existing code logs
* clean: clean the unncessary debug info
* Refactor and generalize dequant helpers
* Remove deprecated quant structs
* Refactor shader defines to reduce repetition
* Remove error override for F16 type
* fix: fix the accidential removal of the proper initialization of ctx
* clean: clean legacy and format code
* fix: did not modify tests ops
---------
Co-authored-by: Jeremy J. Hartmann <jeremy@mtion.tv>
I'm not sure what the purpose of keeping `--alias` was when using
`--models-preset`, but the result is really weird, as shown in the
following logs:
$ build/bin/llama-server --models-preset preset.ini --alias "Gemma 4 E4B UD Q8_K_XL"
...
init: using 31 threads for HTTP server
srv load_models: Loaded 2 cached model presets
srv load_models: Loaded 1 custom model presets from preset.ini
main: failed to initialize router models: alias 'Gemma 4 E4B UD Q8_K_XL' for model 'angt/test-split-model-stories260K:F32' conflicts with existing model name
So I propose to simply ignore `--alias` too in this case. With this
commit, the server starts in routing mode correctly.
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* fix: enable reasoning budget sampler for gemma4
Add thinking_start_tag and thinking_end_tag to
common_chat_params_init_gemma4(). Without these, the reasoning
budget sampler never activates for gemma4.
Make the newline after "thought" optional in the PEG parser to
handle budget=0 (sampler forces end tag before the newline).
Add test case for empty thinking block.
Fixes#21487
* use p.space() instead of p.optional(p.literal("\n")) in gemma4 thought parser
* 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>
Berk Idem
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