* common: fix coding mistakes (typos in identifiers, flags and log strings)
Fix misspelled identifiers and user-facing strings across common, server
and model loading:
- allow_ruless -> allow_rules (misspelled identifier used in the allowlist
CLI parsing and the server slot/context code)
- get_formated_timings/get_formated_generation -> get_formatted_*
- 'termionated' -> 'terminated' in the fit-margin assert message
- 'defaulr' -> 'default' in the YAML dump
- 'overriden' -> 'overridden' in tensor buffer type override logs
- 'becausee' -> 'because' in the output-tensor split log
- 'etected NaNs' -> 'detected NaNs' in the imatrix error message
* common: fix comment typos across src, common, include and examples
Fix misspelled words in code comments:
- llama.h: 'typy' -> 'type', 'transfrom' -> 'transform', 'ecoder' ->
'encoder', 'indicies' -> 'indices', 'Intializes' -> 'Initializes'
- common.h: 'embendings' -> 'embeddings', 'pr' -> 'or' in the
fused-indexer-topk comment
- chat.cpp: 'overridde' -> 'override'
- ngram-map: 'occurences' -> 'occurrences', 'stastistics' -> 'statistics'
- speculative.cpp: 'dont'/'inehit' -> 'don't'/'inherit'
- llama-mmap.cpp: 'dont't' -> 'don't'
- llama-model.h: 'hcurrently andle' -> 'currently handle'
- build_gemma3/4.cpp: 'emdeddings' -> 'embeddings'
- examples: 'quantizuation', 'logprobe', 'throught', 'retrun', 'swich',
'convinient', 'temporally' (-> 'temporary'), 'temproal', 'preceed'
* common: remove duplicate definitions and duplicate help entries
- clip-impl.h: drop the second, identical #define TN_FFN_GATE
- common.cpp: remove the duplicate '-t, --threads N' help entry that was
misplaced in the export-lora section (already listed in the general
section)
- common.cpp: merge the two 'embedding' help groups into a single group
so the embedding options are listed together
- llama.cpp: remove the redundant LLAMA_MAX_LAYERS define (llama-hparams.h
already defines the same value and is included by llama.cpp)
* common: fix remaining typos (accomodate, recommanded, occurences, occassionally)
- accomodate -> accommodate in src/llama.cpp comment
- recommanded -> recommended in quantize.cpp user-facing output
- occurences -> occurrences in test-chat.cpp JSON string
- occassionally -> occasionally in vendor/stb/stb_image_resize2.h comment
Note: tokenizer.ggml.seperator_token_id kept as-is to match GGUF spec
* common: remove duplicate help entries
- remove the duplicate '--reasoning-budget N' help entry that was repeated
in the main section (introduced in e0596bf614 'Autoparser - complete
refactoring of parser architecture (PR 1376)')
- remove the second '--parallel-tool-calls' help entry that advertised the
'-ptc' short flag, which belongs to '--print-token-count' (introduced in
e0596bf614 'Autoparser - complete refactoring of parser architecture
(PR 1376)'); the '-ptc' alias was non-functional for '--parallel-tool-calls'
because the parser only binds it to '--print-token-count'
The canonical help entries are kept:
- '--reasoning-budget N' is listed once
- '--parallel-tool-calls' is listed once (without the conflicting '-ptc' alias)
* common: remove duplicate LOG_ENABLE define
- the '#undef LOG_ENABLE / #define LOG_ENABLE() // dummy stub' pair was
repeated verbatim inside the LOG_DISABLE_LOGS section
- remove the second occurrence (introduced in a2588b53e1 'main : log
file (PR 2748)')
* llama-bench: align MLA and attention-max-batch flags with common tools
llama-bench used '--mla-attn' and '--attn-max-batch' while the common
CLI parsing (common/common.cpp) uses '--mla-use' and
'--attention-max-batch' for the same features. This made the flags
inconsistent across tools.
- update the help text to advertise the canonical names
'--mla-use' and '--attention-max-batch'
- keep the old '--mla-attn' and '--attn-max-batch' spellings working
as aliases so existing scripts are not broken
The divergent names were introduced in 3e536b95b0 'Add optional MLA
(PR 188)'.
* fix typos in comments and user-facing strings
- ngram-map.cpp: 'Do we haven a existing' -> 'Do we have an existing'
(introduced in 1cb7e1bf39 'spec : add self speculative decoding,
ngram and refactor (PR 1261)')
- build_mamba.cpp: 'weigth' -> 'weight' (introduced in 8befd92ea5
'Refactor model compute graphs (PR 1651)')
- gguf-split.cpp: 'one of splits have 0 tensors' -> 'one of the splits
has 0 tensors' (introduced in 75b580db0a 'split: allow
--split-max-size option (PR 6343)')
- gguf-split.cpp: 'merged from %d split' -> 'merged from %d splits'
(introduced in 1b5523dc79 'gguf-split: split and merge gguf per
batch of tensors (PR 6135)')
- convert-llama2c-to-ggml.cpp: missing opening quote in the help line,
'(default %s\\')' -> '(default '%s\\')' (introduced in bb9ebb4394
'Adding support for llama2.c models (PR 2559)')
* harmonize British and American spelling to American English
The codebase uses American English (e.g. --embd-normalize, --color),
but a few strings/comments still used British spellings. Unify them:
- 'normalisation' -> 'normalization' in common.h, common.cpp help text
and code comment, and llama-build-context.cpp comment
- 'colorise' -> 'colorize' in the --color help text (common.cpp)
- 'behaviour' -> 'behavior' in a chat.cpp warning and a llama.cpp comment
- also fix 'openai' -> 'OpenAI' capitalization in the embedding help
text and common.h comment (embedding output format is OpenAI-style)
* common: fix help text formatting inconsistencies
- '-smf16'/'--split-mode-f16' and '-smf32'/'--split-mode-f32' help
entries displayed hardcoded 'true'/'false' as the default value;
show the actual state derived from params.reduce_type instead
- '-no-mmad' help entry had 'fused_mmad?' without a space before the
ternary operator
- '--reasoning-tokens' help continuation lines used tab characters for
indentation while the sibling '--reasoning-format' entry uses spaces;
convert to consistent space indentation
* common: revert smf16/smf32 help text default display change
Revert the '-smf16'/'--split-mode-f16' and '-smf32'/'--split-mode-f32'
help entries back to their original hardcoded 'true'/'false' default
display. The change to derive the default from params.reduce_type was
not desired; the split-mode options are legacy and the hardcoded
defaults reflect their intended meaning.
The other formatting fixes in the same area (fused_mmad ternary
spacing and the reasoning-tokens tab-to-space indentation) are kept.
* llama-bench: fix help text column alignment
The --mla-use and --attention-max-batch help lines introduced by the
flag alignment landed one column off from the sibling entries
((default: at column 51 instead of 50). Adjust the padding so all
help lines align.
* common: fix help text defaults for graph-reduce-type and log-format
Mismatch 1: -grt, --graph-reduce-type help shows default "f32", but actual default (common.h:463) is "f16" and llama.cpp uses GGML_TYPE_F16.
Mismatch 2: --log-format help shows default "json", but actual default (common.h:536 log_json=false) is text.
* common: add -ptcall short flag for --parallel-tool-calls
* typo
Data server_tokens.map_idx_to_media.tokens_image.batch_f32 is read exactly once,
by mtmd_encode, however it was retained as long as the input image was present
in the sequence. Add a manual free function to clear out this data after encoding.
Solves:
* Memory wasted in struct server_tokens
* The same wasted memory in the ram cache
* Long copy durations cloning this data to/from ram cache
* Accounting failures in ram cache (`batch_f32` can be larger than a sequence's entire KV)
* The above accounting failures leading to terminal memory leaks in pathological cases
* Remove JSON serialization for `batch_32` which was unused, and had no foreseeable usecase
* (qwen3vl) Correct calculation for injection point of deepstack image embeddings
INjection point for deepstack embeddings used Hyperparameter n_embd_inp(), which caused the hidden state to be double accounted for, causing an OOB array access. The correct accessor is n_embd()
* Fix m-rope when pipeline parallelism is enabled
Add `-tm` / `--threads-mtmd` to control CPU thread count used during
multimodal image/audio processing (mmproj encoding), separate from the
main LLM thread count.
This allows running the LLM on GPU with minimal CPU threads (e.g. `-t 1`)
to reduce sync overhead, while using many threads (e.g. `-tm 16`) for
CPU-bound mmproj encoding with `--no-mmproj-offload`.
Fallback chain when `-tm` is not specified:
1. `--threads-batch` (-tb) — multimodal encoding is a batch/prefill-like
operation, so it makes sense to track with batch thread count
2. `--threads` (-t) — final default
Works with both mtmd-cli and llama-server.
AI: ubergarm/Qwen3.6-27B-GGUF MTP IQ4_KS 15.113 GiB (4.752 BPW) + pi.dev
* WIP: Gemma4 vision
Crashes on the GPU because of rms_norm requiring ne0 to be multiple
of warp_size.
Runs on the CPU, but produces garbage.
* Remove unnecessary assert in CUDA rms_norm
* GLU was not advertised as supported on CUDA
* Still not working
* This seems to work
* wip: port MTP architecture
Ports the Multi-Token Prediction (MTP) architecture to the older `llama.cpp` codebase used by `ikllama`.
Changes include:
- Updating `llama_batch` to support `mtp_params`.
- Modifying `llama_decode_internal` (and `encode`) to handle MTP operations (Warmup, Update, Draft).
- Adding public APIs for MTP state management (`llama_set_draft_input_hidden_state`).
- Adapting the embedding extraction logic to skip MTP update passes.
* Refactors `server_slot` to support generic speculative decoding (MTP or Draft Model).
* core: enable hybrid outputs (logits + embeddings) for MTP support
* fix(mtp): correct KV-cache slot finding for updates
* fix(mtp): persist hidden states to prevent context corruption during drafting
* refactor(mtp): clean unused code
* fix(mtp): update server to new functions name
* fix(mtp): fix graph and save hidden state
* mtp: refactor integration, context params and kv cache search
* mtp: fix hidden state extraction and speculative acceptance flow
* server: fix MTP warmup for long prompts and reset token buffer
* llama: refactor MTP operation state to context parameters
* server: fix n_past calculation in MTP acceptance
* llama: fix mtp enable flags
* speculative: refactor MTP to use common_speculative interface
* context: remove unused signatures
* clip: fix deprecated enum-enum conversion warning
* common: fix format string crash in help message
* context: fix mtp activation logic
* spec : add self speculative decoding and ngram-mod and refactor
common : use common_ prefix for common library function
llama : use LLAMA_TOKEN_NULL
spec : add self speculative decoding (no draft model required) + refactor
spec : add ngram-mod
spec : various improvements ton ngram-map + docs
spec : fix the check-rate logic of ngram-simple
common : add common_speculative_is_compat()
spec : simplify time measurement using common_time_meas
refactor common_sampler_init
refactor common_token_to_piece
refactor and fix cur_p bug
clean up
* spec : remove check rate
* spec: show warnings instead of abort
---------
Co-authored-by: firecoperana <firecoperana>
Co-authored-by: Sascha Rogmann <59577610+srogmann@users.noreply.github.com>
* model : Granite docling + Idefics3 preprocessing (SmolVLM) (#16206)
* feat: Add granite-docling conversion using trillion pretokenizer
Branch: gabe-l-hart/GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Add granite-docling vocab pre enum
Branch: gabe-l-hart/GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Use granite-docling pre
Branch: gabe-l-hart/GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Add clip_is_idefics3
Branch: gabe-l-hart/GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Allow multi-token boundary sequences for image templating
Branch: gabe-l-hart/GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Add tiling support for idefices3 in clip.cpp
This should likely be moved into llava_uhd::get_slice_instructions, but for
now this avoids disrupting the logic there.
Branch: gabe-l-hart/GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Partial support for full templating for idefics3 in mtmd
There are still errors encoding some of the image chunks, but the token
sequence now matches transformers _almost_ perfectly, except for the double
newline before the global image which shows up as two consecutive newline
tokens instead of a single double-newline token. I think this is happening
because the blocks are tokenized separately then concatenated.
Branch: gabe-l-hart/GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Fully working image preprocessing for idefics3 w/ resize and slicing
Branch: gabe-l-hart/GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Parse the preprocessor config's longest side and add it to the mmproj hparams
Branch: GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Use the longest side instead of size * scale_factor
For Granite Docling, these come out to the same value, but that was just a
conicidence.
Branch: GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Allow batch encoding and remove clip_is_idefics3
Branch: GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* refactor: Remove unnecessary conditionals for empty token vectors
Branch: GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* refactor: Use image_manipulation util
Branch: GraniteDocling
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* add test model
---------
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
# Conflicts:
# convert_hf_to_gguf.py
# convert_hf_to_gguf_update.py
# gguf-py/gguf/constants.py
# gguf-py/gguf/gguf_writer.py
# src/llama-vocab.cpp
# src/llama-vocab.h
* mtmd : support home-cooked Mistral Small Omni (#14928)
* model : add LightOnOCR-1B model (#16764)
* model : add LightOnOCR-1B model
* add test
# Conflicts:
# convert_hf_to_gguf.py
# gguf-py/gguf/constants.py
* mtmd : fix idefics3 preprocessing (#16806)
* mtmd : fix idefics3 preprocessing
* disable granite test
* fix test for granite
* model: Add support for CogVLM model (#15002)
* Added GGUF mappings for CogVLM model
* Add tensor mapping for CogVLM visual encoder
* Add CogVLM to conversion script, no vision part yet
* Added CogVLM vision model to conversion script
* Add graph for CogVLM CLIP model
* Add graph for CogVLM
* Fixes for CogVLM. Now compiles.
* Model now runs
* Fixes for cogvlm graph
* Account for graph context change after rebase
* Changes for whitespace
* Changes in convert script according to comments
* Switch CogVLM LLM graph to merged QKV tensor
* Use rope_type variable instead of direct definition
* Change CogVLM CLIP encoder to use SWIGLU
* Switch CogVLM CLIP to use merged QKV
* Apply rebase edits and remove ggml_cont call that is now unnecessary
* clean up
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
# Conflicts:
# convert_hf_to_gguf.py
# examples/mtmd/clip.cpp
# gguf-py/gguf/constants.py
# gguf-py/gguf/tensor_mapping.py
# src/llama-arch.cpp
# src/llama-arch.h
# src/llama-model.cpp
# src/llama-model.h
* mtmd: refactor preprocessing + support max/min pixels (#16878)
* mtmd: refactor preprocessing + support max/min pixels
* fix mlp type
* implement mix/max pixels
* improve hparams
* better image preproc for qwen
* fix
* fix out of bound composite
* fix (2)
* fix token calculation
* get_merge_kernel_size()
* fix llama4 and lfm2
* gonna fix them all
* use simple resize for qwen
* qwen: increase min tokens
* no resize if dst size == src size
* restore to initial min/max tokens value for qwen
# Conflicts:
# examples/mtmd/clip.cpp
* clip : use FA (#16837)
* clip : use FA
* cont : add warning about unsupported ops
* implement "auto" mode for clip flash attn
* clip : print more detailed op support info during warmup
* cont : remove obsolete comment [no ci]
* improve debugging message
* trailing space
* metal : remove stray return
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* model: add Janus Pro for image understanding (#16906)
* Add support for Janus Pro
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Address reviewer suggestions
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Add JANUS_PRO constant
* Update clip model handling
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
* Update tools/mtmd/clip.cpp
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
* Refactor JANUS_PRO handling in clip.cpp
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
* Update tools/mtmd/clip.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* em whitespace
---------
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>
# Conflicts:
# convert_hf_to_gguf.py
# gguf-py/gguf/constants.py
# gguf-py/gguf/tensor_mapping.py
* mtmd: pad mask for qwen2.5vl (#16954)
* mtmd: pad mask for qwen2.5vl
* improve
* mtmd: add --image-min/max-tokens (#16921)
* mtmd: improve struct initialization (#16981)
* mtmd: allow QwenVL to process larger image by default (#17020)
* Disable flash attention
* mtmd : fix embedding size for image input (#17123)
* mtmd: fix patch_size initialized to random value in audio models (#17128)
* mtmd: fix patch_size initialized to random value in audio models
* add default hparams
* add llama_model_n_embd_inp
* Fix load qwen3 vl
Change batch size
* Add description
* Fix cli build error
---------
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Tianyue-Zhao <zhaotianyue@outlook.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Zhiyong Wang <85110830+ravenouse@users.noreply.github.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
Co-authored-by: firecoperana <firecoperana>
* server: add support for vision model
webui: add support for vision model
* server : remove hack for extra parallel slot#10187
* llama : fix KV shift for qwen2vl #13870
* add no-context-shift parameter
---------
Co-authored-by: firecoperana <firecoperana>
* Add mtmd: the beginning
* Add mtmd: mtmd.cpp compiles
* Add mtmd: clip initialization compiles
* Add mtmd: clip.cpp compiles
* Add mtmd: builds successfully
* Add CPU implementation for GGML_OP_GLU
* Add CUDA implementation for GGML_OP_GLU
* Add CPU implementation for GGML_OP_CONV_2D and GGML_OP_CONV_2D_DW
* Add CUDA implementation for GGML_OP_CONV_2D and GGML_OP_CONV_2D_DW
* Add mtmd: refresh CPU rope
* Add mtmd: refresh CUDA rope
* Add mtmd: add Qwen2-VL
* Add mtmd: Qwen2.5-VL text seems to work with this change
* Add mtmd: fix swiglu
* Add mtmd: use LOG_TEE so generated tokens show up in terminal
* Add mtmd: do not attempt to load a GPU backend if none are available
* GLU, not GPU
* Fix typo
* Fix new/free mismatch
* LOG stuff
* Add mtmd: this fixes gibberish on second image
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>