test_cancel_request enables context shift so the generation only ends
when the request is cancelled, then polls /slots with a deadline.
Without context shift the generation fills the context and frees the
slot on its own on fast machines, so the test passes even with
cancellation disabled.
test_server_sleep uses the existing wait_for_sleep helper instead of a
fixed sleep.
* common: bound control vector layer indices by the model layer count
A direction tensor layer index is parsed from the tensor name with no
upper bound, and the buffer size and write offset are computed in int.
A large index overflows both, so the accumulation writes before the
start of the buffer.
Pass the model layer count to the loader, reject indices above it like
the existing zero index check, and compute the sizes in size_t.
* mtmd: fill M-RoPE positions by whole merge tiles
The position loops of the Qwen-VL, GLM, PaddleOCR and Qwen2.5-VL
encoders hardcode a 2x2 merge inside a stride of n_merge, so a patch
grid that is not a multiple of the merge writes past the positions
buffer. Iterate over whole merge tiles with n_merge inner steps, which
bounds the writes by the patch count and gives the same positions on
aligned grids.
PaddleOCR also requires a merge aligned image at graph build, as the
Qwen-VL family already does.
* opencl: run the tiled q4_K lm_head through a tiled GEMM at batch > 1
* opencl: split tiled dp4a q4_k gemm into its own file and test for dp4a
Assisted-by: Codex
---------
Co-authored-by: Li He <lih@qti.qualcomm.com>
* hexagon: add conv2d op
* hex-conv2d: add double-buffered staging
* hex-conv2d: full 64-wide activation block transpose straight from staged buffer
* hex-conv2d: implicit gemm
* hex-conv2d: remove scalar path and kernel
* hex-conv2d: unify conv2d kernel params for all paths
* hex-conv2d: scale HMX result before f16 storage and then restore during unpacking to prevent overflow
* hex-conv2d: fix f16 overflow in HMX paths
* hex-conv2d: refactor to rebase to new op fusion machinery
* hex-conv2d: restructure DMA pipelines and trace scopes
* hex-conv2d: removed the HVX_WIDTH and HVX_TILED paths
* hex-conv2d: remove in-loop vector spills
* hex-conv2d: refactor kparams, vtcm-layout and dma-pipeline to match the other ops
* hex-conv2d: add basic support for CONV_2D_DW
Co-Authored-By: Pranav Dhinakar <pdhinaka@qti.qualcomm.com>
* hex-conv_2d_dw: use DMA in all paths
* hex-conv_2d_dw: support for chunking larger inputs
* hex-conv_2d_dw: remove scalar/hvx access for w tensor (replaced with sync dma copy)
* hex-conv-2d: fix warnings
* hex-conv2d-dw: vectorize all paths
* hex-conv-2d-dw: tree-based reductions and unrolling to optimize
* hex-conv-2d-dw: uninline compute loops from dma loops
* hex-conv-2d-dw: move all kernel selection into the host solver and simplify/specialize kernel dispatch
* hex-softmax: update obsolete gates to enable SOFT_MAX for mmproj
---------
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
Co-authored-by: Pranav Dhinakar <pdhinaka@qti.qualcomm.com>
* mxfp4 sve 256 impl completed
* working with pretty good perf improvement
* review comments addressed
* review comments for SVE 256 check
* trailing white spaces removed
---------
Co-authored-by: Anubhav Srivastava <anubhav.srivastava@fujitsu.com>
* llama : fix DSV4 compressor padding for simple batches
Count actual tokens per sequence when padding compressor writes. Add a graph reuse regression test for odd-sized DeepSeek V4 and V4.1 batches.
Assisted-by: Codex
* tests : cover multiple sequences in DSV4 padding regression
Exercise one and two sequences at different positions while keeping a fixed ubatch shape.
Assisted-by: Codex
* llama : remove simple batch splitting for DSV4
Use the existing sequence splitting to keep n_seq_tokens consistent with
the compressor padding calculation. Extend the graph reuse regression to
6-token batches.
Assisted-by: Codex
* codeowners : refresh teams and maintainer PRs link
Update the CODEOWNERS team legend with the current `ggml-org` team
memberships, and extend the maintainer PRs link in the README to cover
all current members of the `maintainers` team.
Assisted-by: pi:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
* codeowners : list remaining backend sub-teams
Add the `ggml-*` sub-teams that were missing from the team legend at the
top of the file: base, cpu, et, hip, openvino and riscv. The legend now
covers every sub-team of the `ggml` and `llama` maintainer groups.
No ownership rules change - only the comment block is extended.
Assisted-by: pi:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
* codeowners : use ggml-hip team for HIP backend
Route `/ggml/src/ggml-hip/` to `ggml-org/ggml-hip` instead of a single
collaborator, so review requests reach the whole team.
Assisted-by: pi:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
* codeowners : add llama-examples team
List the newly created `llama-examples` team in the team legend at the
top of the file.
Assisted-by: pi:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
* codeowners : use llama-examples team for examples
Collapse the per-directory rules that only listed a single collaborator
into a single `/examples/` rule owned by `ggml-org/llama-examples`.
Directories owned by other collaborators keep dedicated rules, since the
last matching pattern takes precedence in CODEOWNERS.
Assisted-by: pi:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
* cont : update zdnn
* codeowners : use llama-base team for src
Route `/src/` to `ggml-org/llama-base` and list the new team in the
legend at the top of the file. Rules for individual `src` files are kept,
since the last matching pattern takes precedence; `/src/models/` drops
its individual owner, which is already covered by `llama-models`.
Assisted-by: pi:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
* mtmd : add LFM3-VL and LFM3-Omni video input
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Assisted-by: Claude Opus 5.5
* mtmd : reserve the soundtrack command to avoid a GCC 11 warning
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* ui: build the reasoning menu from the template effort levels
When the chat template reports effort levels, the menu offers Default,
Off and those levels, and a pick is sent as reasoning_effort. A
template that reports none keeps the token budget menu.
Picking a model other than the one that produced the last answer resets
the conversation effort to Default, and an effort the current menu
lacks resolves to Default.
* ui: wait for a cold router model before building the request
A router serves the props of a loaded model only, so a request sent to
a cold model was built without its template effort levels and fell
back to a token budget. The request now waits for the model to load,
joining a load already in flight, and a stop during the wait sends
nothing.
Status waiters hold a list per model so a load and the requests that
wait on it each get theirs, and a props request in flight is shared
with a second caller instead of answering null.
* fix: clamp the A prefetch to end_k in the Vulkan coopmat1 int8 matmul, like the B prefetch
* fix: zero the A scale for k steps past end_k in the Vulkan coopmat1 int8 matmul instead of relying on the clamped block
* chat : strip trailing whitespace from parsed reasoning and content
Assisted-by: Claude Fable 5.1
* chat : stop qwen3-coder reasoning and content before template separators
Assisted-by: Claude
* tests : remove the Qwen parser case from the chat session tests
Assisted-by: Claude
* common : handle partial prefix until match at end of generation
---------
Co-authored-by: Zeshawn Zahid <zzshawnn@gmail.com>
Co-authored-by: Alde Rojas <hello@alde.dev>
* ui : show save and reset settings buttons only when relevant
Assisted-by: Claude (Opus 5.5 Medium)
* ui : move reset settings button next to reload app, pad settings caption
Assisted-by: Claude (Opus 5.5 Medium)
* ui: support OGG audio attachments by converting them to WAV
Fixes#24164
Assisted-by: Claude (Opus 5.5 Medium)
* ui: convert all non WAV/MP3 audio uploads to WAV
Assisted-by: Claude (Opus 5.5 Medium)
* ui: keep new chat draft when adding a system prompt
Fixes#24338
Assisted-by: Claude (Opus 5.5 Medium)
* ui: remove unused initialMessage from chat form
Assisted-by: Claude (Opus 5.5 Medium)
* ui : replace the sidebar search mode with a search dialog
Search opens a spotlight dialog (Cmd+K or the Search entry under New chat in the sidebar) with keyboard navigation over recent chats and sidebar actions. Phones keep the search page.
Sidebar actions show their shortcuts, with new ones for Settings (Cmd+,) and Models (Shift+Cmd+M).
Assisted-by: Claude (Opus 5.5 Medium)
* ui : ignore search dialog keys while an IME is composing
Enter confirms an IME candidate and the arrow keys move through the candidates, so the search field leaves them to the IME instead of opening the highlighted result or moving the highlight.
Assisted-by: Claude (Opus 5.5 Medium)
* server : add realtime conversation and transcription on /v1/realtime
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Assisted-by: Claude Opus 5.5
* examples : default the realtime client to the server port 9931
Assisted-by: Claude Opus 5.5
* server : sample realtime responses right after their own decode
Slots respond in turns on one context: sampling at the start of the next step read the logits of whichever slot decoded last, so concurrent sessions mixed their outputs.
Assisted-by: Claude Opus 5.5
* move more stuff to server-realtime, making it self-contained
* examples : fix the type check of the realtime client
Assisted-by: Claude Opus 5.5
* examples : use the model card prompts in the realtime client
Assisted-by: Claude Opus 5.5
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* model : add LiquidAI/d1-2B and LiquidAI/d1-omni-2B
Assisted-by: Claude Opus 5.5
* convert : keep the speech task templates out of the d1 GGUFs
Assisted-by: Claude Opus 5.5
* small refactoring: no_batching
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* server: expose the reasoning effort levels of the chat template
The capability probe renders a user turn for each candidate level
(minimal, low, medium, high, xhigh, max) and for an unknown level. A
level is honored when it renders without raising and differently from
the unknown level, which shows the template fallback. Levels sharing a
render are aliases and the highest one is kept.
The caps serialize to JSON, and chat_template_caps in /props reports
the list as reasoning_effort_levels, from lowest to highest.
* jinja: keep the caps free of the json dependency
The caps keep reporting their flags as a map, and the effort levels
stay a plain member. common_chat_templates_get_caps() builds the JSON
the server reports from both, so jinja depends on json only for the
probe inputs.
In --models mode the thread count per model is computed and printed,
but never set in the params, so every context runs on the common
default, the number of physical cores. With several models in
parallel this oversubscribes the CPU, and the busy-wait barriers of
the CPU backend make it collapse.
Set the count in cpuparams and cpuparams_batch.
* model : add LiquidAI/LFM3-Audio-2B and LiquidAI/LFM3-Omni-2B
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Assisted-by: Claude Opus 5.5
* convert : read the LFM3-Audio config.json as released
A transformers that knows lfm3_audio rewrites the config into another layout (no lfm/encoder keys).
Assisted-by: Claude Opus 5.5
* mtmd : disable flash attention for the LFM3-Audio depthformer
Assisted-by: Claude Opus 5.5
* tts : add a voice option for LFM3-Audio and LFM3-Omni
The model card offers a female and a male voice; --tts-voice for llama-tts, "voice" for the server /tts.
Assisted-by: Claude Opus 5.5
* clean up template handling
* convert : detect LFM3-Audio and LFM3-Omni by model_type
Assisted-by: Claude Opus 5.5
* move banned tokens --> logits bias --> mtmd_helper
* leave mtmd-cli unchanged
* no more template_asr_system
* left over
* llama : keep the LFM3-Audio encoder convs and codec unquantized
Assisted-by: Claude Opus 5.5
* common, mtmd : shorten comments
Assisted-by: Claude Opus 5.5
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* common : support deferred tools and tool_reference content parts
Assisted-by: Claude Opus 5.5
* common : credit the deferred tools co-author
Co-authored-by: Aldehir Rojas <765227+aldehir@users.noreply.github.com>
Assisted-by: Claude Opus 5.5
* tests : fix the type check of the deferred tools test
Assisted-by: Claude Opus 5.5
* model : add LiquidAI/LFM3-1.7B and LiquidAI/LFM3-VL-2B
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
Assisted-by: Claude Opus 5.5
* tests : set the SWA rope base of the LFM3 test model
Assisted-by: Claude Opus 5.5
* llama : enable recurrent state rollback for LFM3
Assisted-by: Claude Opus 5.5
* Apply batched suggestions from code review
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
Co-authored-by: Tarek Dakhran <github@dakhran.com>
* gguf-py : align the lfm3vl mapping comments
Assisted-by: Claude Opus 5.5
* llama : fix CRLF line endings from the review suggestions
Assisted-by: Claude Opus 5.5
* tests : add the LFM3 Metal fusion baseline
Assisted-by: Claude Opus 5.5
* llama : keep the LFM3-VL depthwise conv kernels in F32 when quantizing
Assisted-by: Claude Opus 5.5
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
* llama : build the k-pool sparse selection independently of the kq_mask shape
qwen4exp (QSA) and glm5-next pick cache cells by index and no longer read the kq_mask values, but they still shaped the selection like the dense kq_mask. Build the selection as [n_kv, n_tokens] over the cache cells instead, and split it into the streams of the K view right before the attention.
This lets the dense mask change its layout (e.g. per-sequence row lists) without touching the sparse layers.
* improve comment
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : drop the unused build_fused_top_k_mask args, review nits
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* tests : speed up tensor data generation and model saving
Refactor save_models to create only the model, not a llama_context,
which is not needed for saving. Replace the slow std::normal_distribution
draw with a splitmix64 + box-muller normal generator.
Assisted-by: dsh:llama.cpp/ggml-org/DeepSeek-V4-Flash-Vision-Exp-GGUF (Mac Studio, M2 Ultra, 192GB)
* tests : use a shared pool of normal draws for tensor data
Generate a pool of normal draws once with std::mt19937 and
std::normal_distribution, then have every tensor copy a cyclic slice of
it instead of running a per-tensor box-muller. The name-keyed slice
selection keeps the draw deterministic.
Assisted-by: dsh:llama.cpp/ggml-org/DeepSeek-V4-Flash-Vision-Exp-GGUF (Mac Studio, M2 Ultra, 192GB)
* tests : log the size of saved models
Report the produced file size in bytes and MB after each save.
Assisted-by: dsh:llama.cpp/ggml-org/DeepSeek-V4-Flash-Vision-Exp-GGUF (Mac Studio, M2 Ultra, 192GB)
* tests : simplify the model save log
Put the model name, target and size on one line per saved model.
Assisted-by: dsh:llama.cpp/ggml-org/DeepSeek-V4-Flash-Vision-Exp-GGUF (Mac Studio, M2 Ultra, 192GB)
* vulkan: allow dim 3 broadcast in MUL_MAT
supports_op rejected every MUL_MAT whose src0 and src1 differ in ne3,
although mul_mm, mul_mmq and mul_mat_vec already broadcast src0 over
dim 3 through broadcast3. Such a matmul then ran on the CPU with a
copy of the weight, and the split layout changed with the number of
streams in the ubatch.
Keep the strict check for MUL_MAT_ID only, and route the broadcast
cases away from mul_mat_vec_nc, the one path that requires equal ne3.
* tests : harden MUL_MAT with permuted dim 3 broadcast cases
Harden the MUL_MAT coverage with a weight broadcast over dim 3 against
a permuted per-stream activation, the shape of an MLA output
projection with a non unified KV cache, for a single token, several
heads and several tokens per stream.
The expand button wrapping the system message card defaulted to
inline-block. WebKit takes an inline-block's baseline from its last
line even when that line is clipped by the card's max-height, so the
row grew to the height of the whole prompt and left a large empty gap
below the card. Make the button a block so the row matches the card.
Assisted-by: Claude (Opus 5.5 Medium)
* server: add --models-memory-max parameter to allow dynamically unloading models when they exceed a memory size threshold
estimate with to-be-loaded model size included
use no_alloc to get memory requirements for model load
only set model memory_mb if not previously calculated
use memory margin instead of total size limit, apply to each device separately
add server memory debug logging
move llama_context_device_memory function to llama-ext.h
fix model count exceeded check
improve memory_per_device map naming
improve variable naming, fix style
also strip models memory margin from child processes
cont : clean-up
replace device memory map with buft memory map. Use llama_get_memory_breakdown
extract duplicated check into helper function
move model memory estimation to subprocess
precompute name->buft map, map GPU host types to CPU buft
cleanup unused variable
remove duplicated init calls
* adapt to upstream changes
* wip
* common_memory_reports internface
* SERVER_ROLE_MEASURE
* server-models-sched
* fix build
* server : fix memory accounting of measure children and claim spin
A measure child runs no_alloc, so the free memory it reports does not
include its estimate: subtracting self there erased the memory held by
other processes, down to zero with --fit on, and the next load could
overshoot the margin. Subtract self only for instance reports.
A queued load only checked --models-max before claiming, so when the
memory margin blocked it behind a busy model, load() threw and the
waiter retried in a tight loop. Refuse the claim while the limits are
exceeded and no idle model can be unloaded, so the waiter sleeps on
the condition variable until one goes idle.
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Pascal <admin@serveurperso.com>
* model : add MiniCPM-OCR-Jev support
The model is a Qwen3.5-VL trunk with a value head read at the last token: it
scores an OCR text against an image rendered from it, it does not generate.
Add the openbmb-minicpm-ocr-jev decision type, served by POST /v1/systemone.
The class scores are the pooled output of the sequence, read with last pooling,
so the conversion turns score.weight into cls.output and sets
embedding_length_out. The checkpoint has no LM head, so text generation is
rejected instead of using the output weights duplicated from the token
embeddings.
The task is fixed, so its prompt is entirely in the systemone template, the
same way h2o-lightning keeps its default there. The processor of the checkpoint
allows up to 16384 merged tokens per image, more than the Qwen-VL default of
mtmd, so the mmproj keeps the image budget of the preprocessor config. The
checkpoint declares MiniCPMOCRForSequenceClassification in its config.json, as
other models do.
Signed-off-by: tc-mb <tianchi_cai@icloud.com>
* fix code
Signed-off-by: tc-mb <tianchi_cai@icloud.com>
* use gguf meta classifier_output_labels
* remove redudant code changes
---------
Signed-off-by: tc-mb <tianchi_cai@icloud.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* metal : add GGML_OP_TOP_K_MASK
Port the fused top-k mask from the CUDA backend: a grid-stride kernel fills the output with -inf, then one
threadgroup per row copies the mask values of the kept cells over it. Function constants drop the score,
blocks and extra paths that a given graph does not use.
Assisted-by: dsh:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
* metal : clean up top-k mask kernel formatting
Assisted-by: dsh:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
Pascal
Nikhil Sharma
Abhijith Jajam
Hongqiang WangandLi He
Bartowski
anubhavfujitsu
abhijain1204fujitsuandAnubhav Srivastava
Aaron Teo
Yonghye Kwon
Georgi Gerganov
Frosty40
anujj
Xuan-Son NguyenandSigbjørn Skjæret
Tarek DakhranandXuan Son Nguyen
Kris
Aleksander Grygier
uvos
Mengsheng Wu
Mendy Berger
Aman GuptaandGeorgi Gerganov
Katara
Sam Malayek
Julien Chaumond
tc-mbandXuan Son Nguyen
Alexey Kopytko