-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 ggml-org#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)