-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: 4096, 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)](https://github.com/ggml-org/llama.cpp/pull/13194#issuecomment-2868343055) (env: LLAMA_ARG_SWA_FULL)

-fa, --flash-attn enable Flash Attention (default: disabled)

(env: LLAMA_ARG_FLASH_ATTN)

--no-perf disable internal libllama performance timings (default: false)

(env: LLAMA_ARG_NO_PERF)

-e, --escape process escapes sequences (\n, \r, \t, \', \", \\) (default: true) --no-escape do not process escape sequences --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: -1.0, 0.0 = full

interpolation)

(env: LLAMA_ARG_YARN_EXT_FACTOR)

--yarn-attn-factor N YaRN: scale sqrt(t) or attention magnitude (default: 1.0)

(env: LLAMA_ARG_YARN_ATTN_FACTOR)

--yarn-beta-slow N YaRN: high correction dim or alpha (default: 1.0)

(env: LLAMA_ARG_YARN_BETA_SLOW)

--yarn-beta-fast N YaRN: low correction dim or beta (default: 32.0)

(env: LLAMA_ARG_YARN_BETA_FAST)

-nkvo, --no-kv-offload disable KV offload

(env: LLAMA_ARG_NO_KV_OFFLOAD)

-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 (default: 0.1, < 0 - disabled)

(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)

--no-mmap do not memory-map model (slower load but may reduce pageouts if not

using mlock)

(env: LLAMA_ARG_NO_MMAP)

--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 --override-tensor, -ot <tensor name pattern>=<buffer type>,...

override tensor buffer type

-ngl, --gpu-layers, --n-gpu-layers N number of layers to store in VRAM

(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)

--check-tensors check model tensor data for invalid values (default: false) --override-kv KEY=TYPE:VALUE advanced option to override model metadata by key. may be specified

multiple times.

types: int, float, bool, str. example: --override-kv tokenizer.ggml.add_bos_token=bool:false

--no-op-offload disable offloading host tensor operations to device (default: false) --lora FNAME path to LoRA adapter (can be repeated to use multiple adapters) --lora-scaled FNAME SCALE path to LoRA adapter with user defined scaling (can be repeated to use

multiple adapters)

--control-vector FNAME add a control vector

note: this argument can be repeated to add multiple control vectors

--control-vector-scaled FNAME SCALE add a control vector with user defined scaling SCALE

note: this argument can be repeated to add multiple scaled control

vectors

--control-vector-layer-range START END

layer range to apply the control vector(s) to, start and end inclusive

-m, --model FNAME model path (default: `models/$filename` with filename from `--hf-file`

or `--model-url` if set, otherwise models/7B/ggml-model-f16.gguf)

(env: LLAMA_ARG_MODEL)

-mu, --model-url MODEL_URL model download url (default: unused)

(env: LLAMA_ARG_MODEL_URL)

-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 --log-colors Enable colored logging

(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.

(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 -----

--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) --sampling-seq, --sampler-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 N temperature (default: 0.8) --top-k N top-k sampling (default: 40, 0 = disabled) --top-p N top-p sampling (default: 0.9, 1.0 = disabled) --min-p N min-p sampling (default: 0.1, 0.0 = disabled) --xtc-probability N xtc probability (default: 0.0, 0.0 = disabled) --xtc-threshold N xtc threshold (default: 0.1, 1.0 = disabled) --typical N locally typical sampling, parameter p (default: 1.0, 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: 1.0, 1.0 = disabled) --presence-penalty N repeat alpha presence penalty (default: 0.0, 0.0 = disabled) --frequency-penalty N repeat alpha frequency penalty (default: 0.0, 0.0 = disabled) --dry-multiplier N set DRY sampling multiplier (default: 0.0, 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

--dynatemp-range N dynamic temperature range (default: 0.0, 0.0 = disabled) --dynatemp-exp N dynamic temperature exponent (default: 1.0) --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: 0.1) --mirostat-ent N Mirostat target entropy, parameter tau (default: 5.0) -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

----- example-specific params -----

--no-context-shift disables context shift on infinite text generation (default: disabled)

(env: LLAMA_ARG_NO_CONTEXT_SHIFT)

-sp, --special special tokens output enabled (default: false) --no-warmup skip warming up the model with an empty run --spm-infill use Suffix/Prefix/Middle pattern for infill (instead of

Prefix/Suffix/Middle) as some models prefer this. (default: disabled)

--pooling {none,mean,cls,last,rank} pooling type for embeddings, use model default if unspecified

(env: LLAMA_ARG_POOLING)

-cb, --cont-batching enable continuous batching (a.k.a dynamic batching) (default: enabled)

(env: LLAMA_ARG_CONT_BATCHING)

-nocb, --no-cont-batching disable continuous batching

(env: LLAMA_ARG_NO_CONT_BATCHING)

--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)

--mmproj-url URL URL to a multimodal projector file. see tools/mtmd/README.md

(env: LLAMA_ARG_MMPROJ_URL)

--no-mmproj explicitly disable multimodal projector, useful when using -hf

(env: LLAMA_ARG_NO_MMPROJ)

--no-mmproj-offload do not offload multimodal projector to GPU

(env: LLAMA_ARG_NO_MMPROJ_OFFLOAD)

-a, --alias STRING set alias for model name (to be used by REST API)

(env: LLAMA_ARG_ALIAS)

--host HOST ip address to listen, or bind to an UNIX socket if the address ends

with .sock (default: 127.0.0.1)

(env: LLAMA_ARG_HOST)

--port PORT port to listen (default: 8080)

(env: LLAMA_ARG_PORT)

--path PATH path to serve static files from (default:¶

/usr/share/llama.cpp-tools/llama-server/active-theme)

(env: LLAMA_ARG_STATIC_PATH)

--api-prefix PREFIX prefix path the server serves from, without the trailing slash

(default: )

(env: LLAMA_ARG_API_PREFIX)

--no-webui Disable the Web UI (default: enabled)

(env: LLAMA_ARG_NO_WEBUI)

--embedding, --embeddings restrict to only support embedding use case; use only with dedicated

embedding models (default: disabled)

(env: LLAMA_ARG_EMBEDDINGS)

--reranking, --rerank enable reranking endpoint on server (default: disabled)

(env: LLAMA_ARG_RERANKING)

--api-key KEY API key to use for authentication (default: none)

(env: LLAMA_API_KEY)

--api-key-file FNAME path to file containing API keys (default: none) --ssl-key-file FNAME path to file a PEM-encoded SSL private key

(env: LLAMA_ARG_SSL_KEY_FILE)

--ssl-cert-file FNAME path to file a PEM-encoded SSL certificate

(env: LLAMA_ARG_SSL_CERT_FILE)

--chat-template-kwargs STRING sets additional params for the json template parser

(env: LLAMA_CHAT_TEMPLATE_KWARGS)

-to, --timeout N server read/write timeout in seconds (default: 600)

(env: LLAMA_ARG_TIMEOUT)

--threads-http N number of threads used to process HTTP requests (default: -1)

(env: LLAMA_ARG_THREADS_HTTP)

--cache-reuse N min chunk size to attempt reusing from the cache via KV shifting

(default: 0)

[(card)](https://ggml.ai/f0.png) (env: LLAMA_ARG_CACHE_REUSE)

--metrics enable prometheus compatible metrics endpoint (default: disabled)

(env: LLAMA_ARG_ENDPOINT_METRICS)

--slots enable slots monitoring endpoint (default: disabled)

(env: LLAMA_ARG_ENDPOINT_SLOTS)

--props enable changing global properties via POST /props (default: disabled)

(env: LLAMA_ARG_ENDPOINT_PROPS)

--no-slots disables slots monitoring endpoint

(env: LLAMA_ARG_NO_ENDPOINT_SLOTS)

--slot-save-path PATH path to save slot kv cache (default: disabled) --jinja use jinja template for chat (default: disabled)

(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` (except in streaming mode, which behaves as `none`) (default: deepseek) (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, chatglm3, chatglm4, chatml, command-r, deepseek, deepseek2, deepseek3, exaone3, falcon3, gemma, gigachat, glmedge, granite, hunyuan-moe, 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, phi3, phi4, rwkv-world, smolvlm, 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, chatglm3, chatglm4, chatml, command-r, deepseek, deepseek2, deepseek3, exaone3, falcon3, gemma, gigachat, glmedge, granite, hunyuan-moe, 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, phi3, phi4, rwkv-world, smolvlm, vicuna, vicuna-orca, yandex, zephyr (env: LLAMA_ARG_CHAT_TEMPLATE_FILE)

--no-prefill-assistant whether to prefill the assistant's response if the last message is an

assistant message (default: prefill enabled)

when this flag is set, if the last message is an assistant message then it will be treated as a full message and not prefilled

(env: LLAMA_ARG_NO_PREFILL_ASSISTANT)

-sps, --slot-prompt-similarity SIMILARITY

how much the prompt of a request must match the prompt of a slot in

order to use that slot (default: 0.50, 0.0 = disabled)

--lora-init-without-apply load LoRA adapters without applying them (apply later via POST

/lora-adapters) (default: disabled)

--draft-max, --draft, --draft-n 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: 0.8)

(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

number of layers to store in VRAM for the draft model

(env: LLAMA_ARG_N_GPU_LAYERS_DRAFT)

-md, --model-draft FNAME draft model for speculative decoding (default: unused)

(env: LLAMA_ARG_MODEL_DRAFT)

-mv, --model-vocoder FNAME vocoder model for audio generation (default: unused) --tts-use-guide-tokens Use guide tokens to improve TTS word recall --embd-bge-small-en-default use default bge-small-en-v1.5 model (note: can download weights from

the internet)

--embd-e5-small-en-default use default e5-small-v2 model (note: can download weights from the

internet)

--embd-gte-small-default use default gte-small model (note: can download weights from the

internet)

--fim-qwen-1.5b-default use default Qwen 2.5 Coder 1.5B (note: can download weights from the

internet)

--fim-qwen-3b-default use default Qwen 2.5 Coder 3B (note: can download weights from the

internet)

--fim-qwen-7b-default use default Qwen 2.5 Coder 7B (note: can download weights from the

internet)

--fim-qwen-7b-spec use Qwen 2.5 Coder 7B + 0.5B draft for speculative decoding (note: can

download weights from the internet)

--fim-qwen-14b-spec use Qwen 2.5 Coder 14B + 0.5B draft for speculative decoding (note:¶

can download weights from the internet)