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* 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 ine0596bf614'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 ine0596bf614'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 ina2588b53e1'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 in3e536b95b0'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 in1cb7e1bf39'spec : add self speculative decoding, ngram and refactor (PR 1261)') - build_mamba.cpp: 'weigth' -> 'weight' (introduced in8befd92ea5'Refactor model compute graphs (PR 1651)') - gguf-split.cpp: 'one of splits have 0 tensors' -> 'one of the splits has 0 tensors' (introduced in75b580db0a'split: allow --split-max-size option (PR 6343)') - gguf-split.cpp: 'merged from %d split' -> 'merged from %d splits' (introduced in1b5523dc79'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 inbb9ebb4394'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
Multimodal Support in llama.cpp
This directory provides multimodal capabilities for llama.cpp. Initially intended as a showcase for running LLaVA models, its scope has expanded significantly over time to include various other vision-capable models. As a result, LLaVA is no longer the only multimodal architecture supported.
Important
Multimodal support can be viewed as a sub-project within
llama.cpp. It is under very heavy development, and breaking changes are expected.
The naming and structure related to multimodal support have evolved, which might cause some confusion. Here's a brief timeline to clarify:
- #3436: Initial support for LLaVA 1.5 was added, introducing
llava.cppandclip.cpp. Thellava-clibinary was created for model interaction. - #4954: Support for MobileVLM was added, becoming the second vision model supported. This built upon the existing
llava.cpp,clip.cpp, andllava-cliinfrastructure. - Expansion & Fragmentation: Many new models were subsequently added (e.g., #7599, #10361, #12344, and others). However,
llava-clilacked support for the increasingly complex chat templates required by these models. This led to the creation of model-specific binaries likeqwen2vl-cli,minicpmv-cli, andgemma3-cli. While functional, this proliferation of command-line tools became confusing for users. - #12849:
libmtmdwas introduced as a replacement forllava.cpp. Its goals include providing a single, unified command-line interface, improving the user/developer experience (UX/DX), and supporting both audio and image inputs. - #13012:
mtmd-cliwas added, consolidating the various model-specific CLIs into a single tool powered bylibmtmd.
Pre-quantized models
See the list of pre-quantized model here
How it works and what is mmproj?
Multimodal support in llama.cpp works by encoding images into embeddings using a separate model component, and then feeding these embeddings into the language model.
This approach keeps the multimodal components distinct from the core libllama library. Separating these allows for faster, independent development cycles. While many modern vision models are based on Vision Transformers (ViTs), their specific pre-processing and projection steps can vary significantly. Integrating this diverse complexity directly into libllama is currently challenging.
Consequently, running a multimodal model typically requires two GGUF files:
- The standard language model file.
- A corresponding multimodal projector (
mmproj) file, which handles the image encoding and projection.
What is libmtmd?
As outlined in the history, libmtmd is the modern library designed to replace the original llava.cpp implementation for handling multimodal inputs.
Built upon clip.cpp (similar to llava.cpp), libmtmd offers several advantages:
- Unified Interface: Aims to consolidate interaction for various multimodal models.
- Improved UX/DX: Features a more intuitive API, inspired by the
Processorclass in the Hugging Facetransformerslibrary. - Flexibility: Designed to support multiple input types (text, audio, images) while respecting the wide variety of chat templates used by different models.
How to obtain mmproj
Multimodal projector (mmproj) files are specific to each model architecture.
For the following models, you can use convert_hf_to_gguf.py with --mmproj flag to get the mmproj file:
- Gemma 3 ; See the guide here - Note: 1B variant does not have vision support
- SmolVLM (from HuggingFaceTB)
- SmolVLM2 (from HuggingFaceTB)
- Pixtral 12B - only works with
transformers-compatible checkpoint - Qwen 2 VL and Qwen 2.5 VL (from Qwen)
- Mistral Small 3.1 24B
- InternVL 2.5 and InternVL 3 from OpenGVLab (note: we don't support conversion of
InternVL3-*-hfmodel, only non-HF version is supported ;InternLM2Modeltext model is not supported)
For older models, please refer to the relevant guide for instructions on how to obtain or create them:
NOTE: conversion scripts are located under tools/mtmd/legacy-models