llama.cpp/tools/cli

Usage

Common params

Argument	Explanation
`-h, --help, --usage`	print usage and exit
`--version`	show version and build info
`--license`	show source code license and dependencies
`-cl, --cache-list`	show list of models in cache
`--completion-bash`	print source-able bash completion script for llama.cpp
`--verbose-prompt`	print a verbose prompt before generation (default: false)
`-t, --threads N`	number of CPU threads to use during generation (default: -1)
(env: LLAMA_ARG_THREADS)
`-tb, --threads-batch N`	number of threads to use during batch and prompt processing (default: same as --threads)
`-C, --cpu-mask M`	CPU affinity mask: arbitrarily long hex. Complements cpu-range (default: "")
`-Cr, --cpu-range lo-hi`	range of CPUs for affinity. Complements --cpu-mask
`--cpu-strict <0\|1>`	use strict CPU placement (default: 0)
`--prio N`	set process/thread priority : low(-1), normal(0), medium(1), high(2), realtime(3) (default: 0)
`--poll <0...100>`	use polling level to wait for work (0 - no polling, default: 50)
`-Cb, --cpu-mask-batch M`	CPU affinity mask: arbitrarily long hex. Complements cpu-range-batch (default: same as --cpu-mask)
`-Crb, --cpu-range-batch lo-hi`	ranges of CPUs for affinity. Complements --cpu-mask-batch
`--cpu-strict-batch <0\|1>`	use strict CPU placement (default: same as --cpu-strict)
`--prio-batch N`	set process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: 0)
`--poll-batch <0\|1>`	use polling to wait for work (default: same as --poll)
`-c, --ctx-size N`	size of the prompt context (default: 0, 0 = loaded from model)
(env: LLAMA_ARG_CTX_SIZE)
`-n, --predict, --n-predict N`	number of tokens to predict (default: -1, -1 = infinity)
(env: LLAMA_ARG_N_PREDICT)
`-b, --batch-size N`	logical maximum batch size (default: 2048)
(env: LLAMA_ARG_BATCH)
`-ub, --ubatch-size N`	physical maximum batch size (default: 512)
(env: LLAMA_ARG_UBATCH)
`--keep N`	number of tokens to keep from the initial prompt (default: 0, -1 = all)
`--swa-full`	use full-size SWA cache (default: false)
(more info)
(env: LLAMA_ARG_SWA_FULL)
`-fa, --flash-attn [on\|off\|auto]`	set Flash Attention use ('on', 'off', or 'auto', default: 'auto')
(env: LLAMA_ARG_FLASH_ATTN)
`-p, --prompt PROMPT`	prompt to start generation with; for system message, use -sys
`--perf, --no-perf`	whether to enable internal libllama performance timings (default: false)
(env: LLAMA_ARG_PERF)
`-f, --file FNAME`	a file containing the prompt (default: none)
`-bf, --binary-file FNAME`	binary file containing the prompt (default: none)
`-e, --escape, --no-escape`	whether to process escapes sequences (\n, \r, \t, ', ", \) (default: true)
`--rope-scaling {none,linear,yarn}`	RoPE frequency scaling method, defaults to linear unless specified by the model
(env: LLAMA_ARG_ROPE_SCALING_TYPE)
`--rope-scale N`	RoPE context scaling factor, expands context by a factor of N
(env: LLAMA_ARG_ROPE_SCALE)
`--rope-freq-base N`	RoPE base frequency, used by NTK-aware scaling (default: loaded from model)
(env: LLAMA_ARG_ROPE_FREQ_BASE)
`--rope-freq-scale N`	RoPE frequency scaling factor, expands context by a factor of 1/N
(env: LLAMA_ARG_ROPE_FREQ_SCALE)
`--yarn-orig-ctx N`	YaRN: original context size of model (default: 0 = model training context size)
(env: LLAMA_ARG_YARN_ORIG_CTX)
`--yarn-ext-factor N`	YaRN: extrapolation mix factor (default: -1.00, 0.0 = full interpolation)
(env: LLAMA_ARG_YARN_EXT_FACTOR)
`--yarn-attn-factor N`	YaRN: scale sqrt(t) or attention magnitude (default: -1.00)
(env: LLAMA_ARG_YARN_ATTN_FACTOR)
`--yarn-beta-slow N`	YaRN: high correction dim or alpha (default: -1.00)
(env: LLAMA_ARG_YARN_BETA_SLOW)
`--yarn-beta-fast N`	YaRN: low correction dim or beta (default: -1.00)
(env: LLAMA_ARG_YARN_BETA_FAST)
`-kvo, --kv-offload, -nkvo, --no-kv-offload`	whether to enable KV cache offloading (default: enabled)
(env: LLAMA_ARG_KV_OFFLOAD)
`--repack, -nr, --no-repack`	whether to enable weight repacking (default: enabled)
(env: LLAMA_ARG_REPACK)
`--no-host`	bypass host buffer allowing extra buffers to be used
(env: LLAMA_ARG_NO_HOST)
`-ctk, --cache-type-k TYPE`	KV cache data type for K
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_K)
`-ctv, --cache-type-v TYPE`	KV cache data type for V
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_V)
`-dt, --defrag-thold N`	KV cache defragmentation threshold (DEPRECATED)
(env: LLAMA_ARG_DEFRAG_THOLD)
`-np, --parallel N`	number of parallel sequences to decode (default: 1)
(env: LLAMA_ARG_N_PARALLEL)
`--mlock`	force system to keep model in RAM rather than swapping or compressing
(env: LLAMA_ARG_MLOCK)
`--mmap, --no-mmap`	whether to memory-map model. (if mmap disabled, slower load but may reduce pageouts if not using mlock) (default: enabled)
(env: LLAMA_ARG_MMAP)
`-dio, --direct-io, -ndio, --no-direct-io`	use DirectIO if available. (default: disabled)
(env: LLAMA_ARG_DIO)
`--numa TYPE`	attempt optimizations that help on some NUMA systems

distribute: spread execution evenly over all nodes
isolate: only spawn threads on CPUs on the node that execution started on
numactl: use the CPU map provided by numactl if run without this previously, it is recommended to drop the system page cache before using this see https://github.com/ggml-org/llama.cpp/issues/1437 (env: LLAMA_ARG_NUMA) | | -dev, --device <dev1,dev2,..> | comma-separated list of devices to use for offloading (none = don't offload) use --list-devices to see a list of available devices (env: LLAMA_ARG_DEVICE) | | --list-devices | print list of available devices and exit | | -ot, --override-tensor <tensor name pattern>=<buffer type>,... | override tensor buffer type (env: LLAMA_ARG_OVERRIDE_TENSOR) | | -cmoe, --cpu-moe | keep all Mixture of Experts (MoE) weights in the CPU (env: LLAMA_ARG_CPU_MOE) | | -ncmoe, --n-cpu-moe N | keep the Mixture of Experts (MoE) weights of the first N layers in the CPU (env: LLAMA_ARG_N_CPU_MOE) | | -ngl, --gpu-layers, --n-gpu-layers N | max. number of layers to store in VRAM, either an exact number, 'auto', or 'all' (default: auto) (env: LLAMA_ARG_N_GPU_LAYERS) | | -sm, --split-mode {none,layer,row} | how to split the model across multiple GPUs, one of:
none: use one GPU only
layer (default): split layers and KV across GPUs
row: split rows across GPUs (env: LLAMA_ARG_SPLIT_MODE) | | -ts, --tensor-split N0,N1,N2,... | fraction of the model to offload to each GPU, comma-separated list of proportions, e.g. 3,1 (env: LLAMA_ARG_TENSOR_SPLIT) | | -mg, --main-gpu INDEX | the GPU to use for the model (with split-mode = none), or for intermediate results and KV (with split-mode = row) (default: 0) (env: LLAMA_ARG_MAIN_GPU) | | -fit, --fit [on\|off] | whether to adjust unset arguments to fit in device memory ('on' or 'off', default: 'on') (env: LLAMA_ARG_FIT) | | -fitt, --fit-target MiB0,MiB1,MiB2,... | target margin per device for --fit, comma-separated list of values, single value is broadcast across all devices, default: 1024 (env: LLAMA_ARG_FIT_TARGET) | | -fitc, --fit-ctx N | minimum ctx size that can be set by --fit option, default: 4096 (env: LLAMA_ARG_FIT_CTX) | | --check-tensors | check model tensor data for invalid values (default: false) | | --override-kv KEY=TYPE:VALUE,... | advanced option to override model metadata by key. to specify multiple overrides, either use comma-separated values. types: int, float, bool, str. example: --override-kv tokenizer.ggml.add_bos_token=bool:false,tokenizer.ggml.add_eos_token=bool:false | | --op-offload, --no-op-offload | whether to offload host tensor operations to device (default: true) | | --lora FNAME | path to LoRA adapter (use comma-separated values to load multiple adapters) | | --lora-scaled FNAME:SCALE,... | path to LoRA adapter with user defined scaling (format: FNAME:SCALE,...) note: use comma-separated values | | --control-vector FNAME | add a control vector note: use comma-separated values to add multiple control vectors | | --control-vector-scaled FNAME:SCALE,... | add a control vector with user defined scaling SCALE note: use comma-separated values (format: FNAME:SCALE,...) | | --control-vector-layer-range START END | layer range to apply the control vector(s) to, start and end inclusive | | -m, --model FNAME | model path to load (env: LLAMA_ARG_MODEL) | | -mu, --model-url MODEL_URL | model download url (default: unused) (env: LLAMA_ARG_MODEL_URL) | | -dr, --docker-repo [<repo>/]<model>[:quant] | Docker Hub model repository. repo is optional, default to ai/. quant is optional, default to :latest. example: gemma3 (default: unused) (env: LLAMA_ARG_DOCKER_REPO) | | -hf, -hfr, --hf-repo <user>/<model>[:quant] | Hugging Face model repository; quant is optional, case-insensitive, default to Q4_K_M, or falls back to the first file in the repo if Q4_K_M doesn't exist. mmproj is also downloaded automatically if available. to disable, add --no-mmproj example: unsloth/phi-4-GGUF:q4_k_m (default: unused) (env: LLAMA_ARG_HF_REPO) | | -hfd, -hfrd, --hf-repo-draft <user>/<model>[:quant] | Same as --hf-repo, but for the draft model (default: unused) (env: LLAMA_ARG_HFD_REPO) | | -hff, --hf-file FILE | Hugging Face model file. If specified, it will override the quant in --hf-repo (default: unused) (env: LLAMA_ARG_HF_FILE) | | -hfv, -hfrv, --hf-repo-v <user>/<model>[:quant] | Hugging Face model repository for the vocoder model (default: unused) (env: LLAMA_ARG_HF_REPO_V) | | -hffv, --hf-file-v FILE | Hugging Face model file for the vocoder model (default: unused) (env: LLAMA_ARG_HF_FILE_V) | | -hft, --hf-token TOKEN | Hugging Face access token (default: value from HF_TOKEN environment variable) (env: HF_TOKEN) | | --log-disable | Log disable | | --log-file FNAME | Log to file (env: LLAMA_LOG_FILE) | | --log-colors [on\|off\|auto] | Set colored logging ('on', 'off', or 'auto', default: 'auto') 'auto' enables colors when output is to a terminal (env: LLAMA_LOG_COLORS) | | -v, --verbose, --log-verbose | Set verbosity level to infinity (i.e. log all messages, useful for debugging) | | --offline | Offline mode: forces use of cache, prevents network access (env: LLAMA_OFFLINE) | | -lv, --verbosity, --log-verbosity N | Set the verbosity threshold. Messages with a higher verbosity will be ignored. Values:
0: generic output
1: error
2: warning
3: info
4: debug (default: 3)

(env: LLAMA_LOG_VERBOSITY) | | --log-prefix | Enable prefix in log messages (env: LLAMA_LOG_PREFIX) | | --log-timestamps | Enable timestamps in log messages (env: LLAMA_LOG_TIMESTAMPS) | | -ctkd, --cache-type-k-draft TYPE | KV cache data type for K for the draft model allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1 (default: f16) (env: LLAMA_ARG_CACHE_TYPE_K_DRAFT) | | -ctvd, --cache-type-v-draft TYPE | KV cache data type for V for the draft model allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1 (default: f16) (env: LLAMA_ARG_CACHE_TYPE_V_DRAFT) |

Sampling params

Argument	Explanation
`--samplers SAMPLERS`	samplers that will be used for generation in the order, separated by ';'
(default: penalties;dry;top_n_sigma;top_k;typ_p;top_p;min_p;xtc;temperature)
`-s, --seed SEED`	RNG seed (default: -1, use random seed for -1)
`--sampler-seq, --sampling-seq SEQUENCE`	simplified sequence for samplers that will be used (default: edskypmxt)
`--ignore-eos`	ignore end of stream token and continue generating (implies --logit-bias EOS-inf)
`--temp, --temperature N`	temperature (default: 0.80)
`--top-k N`	top-k sampling (default: 40, 0 = disabled)
(env: LLAMA_ARG_TOP_K)
`--top-p N`	top-p sampling (default: 0.95, 1.0 = disabled)
`--min-p N`	min-p sampling (default: 0.05, 0.0 = disabled)
`--top-nsigma, --top-n-sigma N`	top-n-sigma sampling (default: -1.00, -1.0 = disabled)
`--xtc-probability N`	xtc probability (default: 0.00, 0.0 = disabled)
`--xtc-threshold N`	xtc threshold (default: 0.10, 1.0 = disabled)
`--typical, --typical-p N`	locally typical sampling, parameter p (default: 1.00, 1.0 = disabled)
`--repeat-last-n N`	last n tokens to consider for penalize (default: 64, 0 = disabled, -1 = ctx_size)
`--repeat-penalty N`	penalize repeat sequence of tokens (default: 1.00, 1.0 = disabled)
`--presence-penalty N`	repeat alpha presence penalty (default: 0.00, 0.0 = disabled)
`--frequency-penalty N`	repeat alpha frequency penalty (default: 0.00, 0.0 = disabled)
`--dry-multiplier N`	set DRY sampling multiplier (default: 0.00, 0.0 = disabled)
`--dry-base N`	set DRY sampling base value (default: 1.75)
`--dry-allowed-length N`	set allowed length for DRY sampling (default: 2)
`--dry-penalty-last-n N`	set DRY penalty for the last n tokens (default: -1, 0 = disable, -1 = context size)
`--dry-sequence-breaker STRING`	add sequence breaker for DRY sampling, clearing out default breakers ('\n', ':', '"', '*') in the process; use "none" to not use any sequence breakers
`--adaptive-target N`	adaptive-p: select tokens near this probability (valid range 0.0 to 1.0; negative = disabled) (default: -1.00)
(more info)
`--adaptive-decay N`	adaptive-p: decay rate for target adaptation over time. lower values are more reactive, higher values are more stable.
(valid range 0.0 to 0.99) (default: 0.90)
`--dynatemp-range N`	dynamic temperature range (default: 0.00, 0.0 = disabled)
`--dynatemp-exp N`	dynamic temperature exponent (default: 1.00)
`--mirostat N`	use Mirostat sampling.
Top K, Nucleus and Locally Typical samplers are ignored if used.
(default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
`--mirostat-lr N`	Mirostat learning rate, parameter eta (default: 0.10)
`--mirostat-ent N`	Mirostat target entropy, parameter tau (default: 5.00)
`-l, --logit-bias TOKEN_ID(+/-)BIAS`	modifies the likelihood of token appearing in the completion,
i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',
or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'
`--grammar GRAMMAR`	BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '')
`--grammar-file FNAME`	file to read grammar from
`-j, --json-schema SCHEMA`	JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object
For schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead
`-jf, --json-schema-file FILE`	File containing a JSON schema to constrain generations (https://json-schema.org/), e.g. `{}` for any JSON object
For schemas w/ external $refs, use --grammar + example/json_schema_to_grammar.py instead
`-bs, --backend-sampling`	enable backend sampling (experimental) (default: disabled)
(env: LLAMA_ARG_BACKEND_SAMPLING)

CLI-specific params

Argument	Explanation
`--display-prompt, --no-display-prompt`	whether to print prompt at generation (default: true)
`-co, --color [on\|off\|auto]`	Colorize output to distinguish prompt and user input from generations ('on', 'off', or 'auto', default: 'auto')
'auto' enables colors when output is to a terminal
`--ctx-checkpoints, --swa-checkpoints N`	max number of context checkpoints to create per slot (default: 8)(more info)
(env: LLAMA_ARG_CTX_CHECKPOINTS)
`-cram, --cache-ram N`	set the maximum cache size in MiB (default: 8192, -1 - no limit, 0 - disable)(more info)
(env: LLAMA_ARG_CACHE_RAM)
`--context-shift, --no-context-shift`	whether to use context shift on infinite text generation (default: disabled)
(env: LLAMA_ARG_CONTEXT_SHIFT)
`-sys, --system-prompt PROMPT`	system prompt to use with model (if applicable, depending on chat template)
`--show-timings, --no-show-timings`	whether to show timing information after each response (default: true)
(env: LLAMA_ARG_SHOW_TIMINGS)
`-sysf, --system-prompt-file FNAME`	a file containing the system prompt (default: none)
`-r, --reverse-prompt PROMPT`	halt generation at PROMPT, return control in interactive mode
`-sp, --special`	special tokens output enabled (default: false)
`-cnv, --conversation, -no-cnv, --no-conversation`	whether to run in conversation mode:

does not print special tokens and suffix/prefix
interactive mode is also enabled (default: auto enabled if chat template is available) | | -st, --single-turn | run conversation for a single turn only, then exit when done will not be interactive if first turn is predefined with --prompt (default: false) | | -mli, --multiline-input | allows you to write or paste multiple lines without ending each in '' | | --warmup, --no-warmup | whether to perform warmup with an empty run (default: enabled) | | -mm, --mmproj FILE | path to a multimodal projector file. see tools/mtmd/README.md note: if -hf is used, this argument can be omitted (env: LLAMA_ARG_MMPROJ) | | -mmu, --mmproj-url URL | URL to a multimodal projector file. see tools/mtmd/README.md (env: LLAMA_ARG_MMPROJ_URL) | | --mmproj-auto, --no-mmproj, --no-mmproj-auto | whether to use multimodal projector file (if available), useful when using -hf (default: enabled) (env: LLAMA_ARG_MMPROJ_AUTO) | | --mmproj-offload, --no-mmproj-offload | whether to enable GPU offloading for multimodal projector (default: enabled) (env: LLAMA_ARG_MMPROJ_OFFLOAD) | | --image, --audio FILE | path to an image or audio file. use with multimodal models, use comma-separated values for multiple files | | --image-min-tokens N | minimum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model) (env: LLAMA_ARG_IMAGE_MIN_TOKENS) | | --image-max-tokens N | maximum number of tokens each image can take, only used by vision models with dynamic resolution (default: read from model) (env: LLAMA_ARG_IMAGE_MAX_TOKENS) | | -otd, --override-tensor-draft <tensor name pattern>=<buffer type>,... | override tensor buffer type for draft model | | -cmoed, --cpu-moe-draft | keep all Mixture of Experts (MoE) weights in the CPU for the draft model (env: LLAMA_ARG_CPU_MOE_DRAFT) | | -ncmoed, --n-cpu-moe-draft N | keep the Mixture of Experts (MoE) weights of the first N layers in the CPU for the draft model (env: LLAMA_ARG_N_CPU_MOE_DRAFT) | | --chat-template-kwargs STRING | sets additional params for the json template parser, must be a valid json object string, e.g. '{"key1":"value1","key2":"value2"}' (env: LLAMA_CHAT_TEMPLATE_KWARGS) | | --jinja, --no-jinja | whether to use jinja template engine for chat (default: enabled) (env: LLAMA_ARG_JINJA) | | --reasoning-format FORMAT | controls whether thought tags are allowed and/or extracted from the response, and in which format they're returned; one of:
none: leaves thoughts unparsed in message.content
deepseek: puts thoughts in message.reasoning_content
deepseek-legacy: keeps <think> tags in message.content while also populating message.reasoning_content (default: auto) (env: LLAMA_ARG_THINK) | | --reasoning-budget N | controls the amount of thinking allowed; currently only one of: -1 for unrestricted thinking budget, or 0 to disable thinking (default: -1) (env: LLAMA_ARG_THINK_BUDGET) | | --chat-template JINJA_TEMPLATE | set custom jinja chat template (default: template taken from model's metadata) if suffix/prefix are specified, template will be disabled only commonly used templates are accepted (unless --jinja is set before this flag): list of built-in templates: bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml, command-r, deepseek, deepseek2, deepseek3, exaone-moe, exaone3, exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite, grok-2, hunyuan-dense, hunyuan-moe, kimi-k2, llama2, llama2-sys, llama2-sys-bos, llama2-sys-strip, llama3, llama4, megrez, minicpm, mistral-v1, mistral-v3, mistral-v3-tekken, mistral-v7, mistral-v7-tekken, monarch, openchat, orion, pangu-embedded, phi3, phi4, rwkv-world, seed_oss, smolvlm, solar-open, vicuna, vicuna-orca, yandex, zephyr (env: LLAMA_ARG_CHAT_TEMPLATE) | | --chat-template-file JINJA_TEMPLATE_FILE | set custom jinja chat template file (default: template taken from model's metadata) if suffix/prefix are specified, template will be disabled only commonly used templates are accepted (unless --jinja is set before this flag): list of built-in templates: bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml, command-r, deepseek, deepseek2, deepseek3, exaone-moe, exaone3, exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite, grok-2, hunyuan-dense, hunyuan-moe, kimi-k2, llama2, llama2-sys, llama2-sys-bos, llama2-sys-strip, llama3, llama4, megrez, minicpm, mistral-v1, mistral-v3, mistral-v3-tekken, mistral-v7, mistral-v7-tekken, monarch, openchat, orion, pangu-embedded, phi3, phi4, rwkv-world, seed_oss, smolvlm, solar-open, vicuna, vicuna-orca, yandex, zephyr (env: LLAMA_ARG_CHAT_TEMPLATE_FILE) | | --simple-io | use basic IO for better compatibility in subprocesses and limited consoles | | --draft, --draft-n, --draft-max N | number of tokens to draft for speculative decoding (default: 16) (env: LLAMA_ARG_DRAFT_MAX) | | --draft-min, --draft-n-min N | minimum number of draft tokens to use for speculative decoding (default: 0) (env: LLAMA_ARG_DRAFT_MIN) | | --draft-p-min P | minimum speculative decoding probability (greedy) (default: 0.75) (env: LLAMA_ARG_DRAFT_P_MIN) | | -cd, --ctx-size-draft N | size of the prompt context for the draft model (default: 0, 0 = loaded from model) (env: LLAMA_ARG_CTX_SIZE_DRAFT) | | -devd, --device-draft <dev1,dev2,..> | comma-separated list of devices to use for offloading the draft model (none = don't offload) use --list-devices to see a list of available devices | | -ngld, --gpu-layers-draft, --n-gpu-layers-draft N | max. number of draft model layers to store in VRAM, either an exact number, 'auto', or 'all' (default: auto) (env: LLAMA_ARG_N_GPU_LAYERS_DRAFT) | | -md, --model-draft FNAME | draft model for speculative decoding (default: unused) (env: LLAMA_ARG_MODEL_DRAFT) | | --spec-replace TARGET DRAFT | translate the string in TARGET into DRAFT if the draft model and main model are not compatible | | --gpt-oss-20b-default | use gpt-oss-20b (note: can download weights from the internet) | | --gpt-oss-120b-default | use gpt-oss-120b (note: can download weights from the internet) | | --vision-gemma-4b-default | use Gemma 3 4B QAT (note: can download weights from the internet) | | --vision-gemma-12b-default | use Gemma 3 12B QAT (note: can download weights from the internet) |