NAME

llama-server - manual page for llama-server 10015 (12127def [alt1])

DESCRIPTION

Common Params:

-h, --help, --usage

print usage and exit

--version

show version and build info

-cl, --cache-list

show list of models in cache

--completion-bash

print source-able bash completion script for llama.cpp

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

--perf, --no-perf

whether to enable internal libllama performance timings (default: false) (env: LLAMA_ARG_PERF)

-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)

--rpc SERVERS

comma-separated list of RPC servers (host:port) (env: LLAMA_ARG_RPC)

--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,tensor}

how to split the model across multiple GPUs, one of: - none: use one GPU only - layer (default): split layers and KV across GPUs (pipelined) - row: split weight across GPUs by rows (parallelized) - tensor: split weights and KV across GPUs (parallelized, EXPERIMENTAL) (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: ggml-org/GLM-4.7-Flash-GGUF:Q4_K_M (default: unused) (env: LLAMA_ARG_HF_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_ARG_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_ARG_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_ARG_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:

trace (more info)

- 5:

debug

(default:

3)

(env:

LLAMA_ARG_LOG_VERBOSITY)

--log-prefix, --no-log-prefix

Enable prefix in log messages (env: LLAMA_ARG_LOG_PREFIX)

--log-timestamps, --no-log-timestamps

Enable timestamps in log messages (env: LLAMA_ARG_LOG_TIMESTAMPS)

--spec-draft-type-k, -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_SPEC_DRAFT_CACHE_TYPE_K)

--spec-draft-type-v, -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_SPEC_DRAFT_CACHE_TYPE_V)

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)

--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)](https://github.com/ggml-org/llama.cpp/pull/17927)

--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)

--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)

Speculative Params:

--spec-draft-hf, -hfd, -hfrd, --hf-repo-draft <user>/<model>[:quant]

Same as --hf-repo, but for the draft model (default:

unused)

(env:

LLAMA_ARG_SPEC_DRAFT_HF_REPO)

--spec-draft-threads, -td, --threads-draft N

number of threads to use during generation (default:

same as

--threads)

--spec-draft-threads-batch, -tbd, --threads-batch-draft N

number of threads to use during batch and prompt processing (default:

same as --threads-draft)

--spec-draft-cpu-mask, -Cd, --cpu-mask-draft M

Draft model CPU affinity mask. Complements cpu-range-draft (default:

same as --cpu-mask)

--spec-draft-cpu-range, -Crd, --cpu-range-draft lo-hi

Ranges of CPUs for affinity. Complements --cpu-mask-draft

--spec-draft-cpu-strict, --cpu-strict-draft <0|1>

Use strict CPU placement for draft model (default:

same as

--cpu-strict)

--spec-draft-prio, --prio-draft N

set draft process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: 0)

--spec-draft-poll, --poll-draft <0|1>

Use polling to wait for draft model work (default: same as --poll)

--spec-draft-cpu-mask-batch, -Cbd, --cpu-mask-batch-draft M

Draft model CPU affinity mask. Complements cpu-range-draft (default:

same as --cpu-mask)

--spec-draft-cpu-strict-batch, --cpu-strict-batch-draft <0|1>

Use strict CPU placement for draft model (default:

--cpu-strict-draft)

--spec-draft-prio-batch, --prio-batch-draft N

set draft process/thread priority :

0-normal, 1-medium, 2-high,

3-realtime (default:

0)

--spec-draft-poll-batch, --poll-batch-draft <0|1>

Use polling to wait for draft model work (default:

--poll-draft)

--spec-draft-override-tensor, -otd, --override-tensor-draft <tensor name pattern>=<buffer type>,...

override tensor buffer type for draft model

--spec-draft-cpu-moe, -cmoed, --cpu-moe-draft

keep all Mixture of Experts (MoE) weights in the CPU for the draft

model (env: LLAMA_ARG_SPEC_DRAFT_CPU_MOE)

--spec-draft-n-cpu-moe, --spec-draft-ncmoe, -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_SPEC_DRAFT_N_CPU_MOE)

--spec-draft-n-max N

number of tokens to draft for speculative decoding (default: 3) (env: LLAMA_ARG_SPEC_DRAFT_N_MAX)

--spec-draft-n-min N

minimum number of draft tokens to use for speculative decoding (default: 0) (env: LLAMA_ARG_SPEC_DRAFT_N_MIN)

--spec-draft-p-split, --draft-p-split P

speculative decoding split probability (default:

0.10)

(env:

LLAMA_ARG_SPEC_DRAFT_P_SPLIT)

--spec-draft-p-min, --draft-p-min P

minimum speculative decoding probability (greedy) (default: 0.00) (env: LLAMA_ARG_SPEC_DRAFT_P_MIN)

--spec-draft-backend-sampling, --no-spec-draft-backend-sampling

offload draft sampling to the backend (default:

enabled)

(env:

LLAMA_ARG_SPEC_DRAFT_BACKEND_SAMPLING)

--spec-draft-device, -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

--spec-draft-ngl, -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)

--spec-draft-model, -md, --model-draft FNAME

draft model for speculative decoding (default:

unused)

(env:

LLAMA_ARG_SPEC_DRAFT_MODEL)

--spec-type none,draft-simple,draft-eagle3,draft-mtp,draft-dflash,ngram-simple,ngram-map-k,ngram-map-k4v,ngram-mod,ngram-cache

comma-separated list of types of speculative decoding to use (default:

none)

(env:

LLAMA_ARG_SPEC_TYPE)

--spec-ngram-mod-n-min N

minimum number of ngram tokens to use for ngram-based speculative decoding (default: 48)

--spec-ngram-mod-n-max N

maximum number of ngram tokens to use for ngram-based speculative decoding (default: 64)

--spec-ngram-mod-n-match N

ngram-mod lookup length (default: 24)

--spec-ngram-simple-size-n N

ngram size N for ngram-simple speculative decoding, length of lookup n-gram (default: 12)

--spec-ngram-simple-size-m N

ngram size M for ngram-simple speculative decoding, length of draft m-gram (default: 48)

--spec-ngram-simple-min-hits N

minimum hits for ngram-simple speculative decoding (default: 1)

--spec-ngram-map-k-size-n N

ngram size N for ngram-map-k speculative decoding, length of lookup n-gram (default: 12)

--spec-ngram-map-k-size-m N

ngram size M for ngram-map-k speculative decoding, length of draft m-gram (default: 48)

--spec-ngram-map-k-min-hits N

minimum hits for ngram-map-k speculative decoding (default: 1)

--spec-ngram-map-k4v-size-n N

ngram size N for ngram-map-k4v speculative decoding, length of lookup n-gram (default: 12)

--spec-ngram-map-k4v-size-m N

ngram size M for ngram-map-k4v speculative decoding, length of draft m-gram (default: 48)

--spec-ngram-map-k4v-min-hits N

minimum hits for ngram-map-k4v speculative decoding (default: 1)

--draft, --draft-n, --draft-max N

the argument has been removed. use --spec-draft-n-max or --spec-ngram-mod-n-max (env: LLAMA_ARG_DRAFT_MAX)

--draft-min, --draft-n-min N

the argument has been removed. use --spec-draft-n-min or --spec-ngram-mod-n-min (env: LLAMA_ARG_DRAFT_MIN)

--spec-ngram-size-n N

the argument has been removed. use the respective --spec-ngram-*-size-n or --spec-ngram-mod-n-match

--spec-ngram-size-m N

the argument has been removed. use the respective --spec-ngram-*-size-m

--spec-ngram-min-hits N

the argument has been removed. use the respective --spec-ngram-*-min-hits

Example-specific Params:

-lcs, --lookup-cache-static FNAME

path to static lookup cache to use for lookup decoding (not updated by generation)

-lcd, --lookup-cache-dynamic FNAME

path to dynamic lookup cache to use for lookup decoding (updated by generation)

-ctxcp, --ctx-checkpoints, --swa-checkpoints N

max number of context checkpoints to create per slot (default:

32)[(more info)](https://github.com/ggml-org/llama.cpp/pull/15293) (env: LLAMA_ARG_CTX_CHECKPOINTS)

-cms, --checkpoint-min-step N

minimum spacing between context checkpoints in tokens (default: 8192, 0 = no minimum) (env: LLAMA_ARG_CHECKPOINT_MIN_SPACING_NT)

-cram, --cache-ram N

set the maximum cache size in MiB (default: 8192, -1 - no limit, 0 - disable)[(more info)](https://github.com/ggml-org/llama.cpp/pull/16391) (env: LLAMA_ARG_CACHE_RAM)

-kvu, --kv-unified, -no-kvu, --no-kv-unified

use single unified KV buffer shared across all sequences (default:

enabled if number of slots is auto) (env: LLAMA_ARG_KV_UNIFIED)

--cache-idle-slots, --no-cache-idle-slots

save idle slots to the prompt cache on new task, and clear them when

using unified KV (default: enabled, requires cache-ram) (env: LLAMA_ARG_CACHE_IDLE_SLOTS)

--context-shift, --no-context-shift

whether to use context shift on infinite text generation (default: disabled) (env: LLAMA_ARG_CONTEXT_SHIFT)

-r, --reverse-prompt PROMPT

halt generation at PROMPT, return control in interactive mode

-sp, --special

special tokens output enabled (default: false)

--warmup, --no-warmup

whether to perform warmup with an empty run (default: enabled)

--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)

-np, --parallel N

number of server slots (default: -1, -1 = auto) (env: LLAMA_ARG_N_PARALLEL)

-cb, --cont-batching, -nocb, --no-cont-batching

whether to enable continuous batching (a.k.a dynamic batching) (default: enabled) (env: LLAMA_ARG_CONT_BATCHING)

-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-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)

--mtmd-batch-max-tokens N

maximum number of image tokens per batch when encoding images (default: 1024) (env: LLAMA_ARG_MTMD_BATCH_MAX_TOKENS)

-a, --alias STRING

set model name aliases, comma-separated (to be used by API) (env: LLAMA_ARG_ALIAS)

--tags STRING

set model tags, comma-separated (informational, not used for routing) (env: LLAMA_ARG_TAGS)

--embd-normalize N

normalisation for embeddings (default: 2) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)

--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)

--reuse-port

allow multiple sockets to bind to the same port (default: disabled) (env: LLAMA_ARG_REUSE_PORT)

--path PATH

path to serve static files from (default: ) (env: LLAMA_ARG_STATIC_PATH)

--cors-origins ORIGINS

comma-separated list of allowed origins for CORS (default: *) if set to special value 'localhost', reflect the Origin header only if it is localhost (env: LLAMA_ARG_CORS_ORIGINS)

--cors-methods METHODS

comma-separated list of allowed methods for CORS (default: GET, POST, DELETE, OPTIONS) (env: LLAMA_ARG_CORS_METHODS)

--cors-headers HEADERS

comma-separated list of allowed headers for CORS (default: *) (env: LLAMA_ARG_CORS_HEADERS)

--cors-credentials, --no-cors-credentials

whether to allow credentials for CORS (default:

enabled)

note:

if this is enabled and --cors-origins is set to * (default), the

Origin header will be echoed back, and credentials will always be

allowed (env: LLAMA_ARG_CORS_CREDENTIALS)

--api-prefix PREFIX

prefix path the server serves from, without the trailing slash (default: ) (env: LLAMA_ARG_API_PREFIX)

--ui-config, --webui-config JSON

JSON that provides default UI settings (overrides UI defaults) (env: LLAMA_ARG_UI_CONFIG)

--ui-config-file, --webui-config-file PATH

JSON file that provides default UI settings (overrides UI defaults)

(env: LLAMA_ARG_UI_CONFIG_FILE)

--ui-mcp-proxy, --webui-mcp-proxy, --no-ui-mcp-proxy, --no-webui-mcp-proxy

experimental:

whether to enable MCP CORS proxy - do not enable in

untrusted environments (default:

disabled)

(env:

LLAMA_ARG_UI_MCP_PROXY)

--tools TOOL1,TOOL2,...

experimental: whether to enable built-in tools for AI agents - do not enable in untrusted environments (default: no tools) specify "all" to enable all tools available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, get_datetime note: for security reasons, this will limit --cors-origins to localhost by default (env: LLAMA_ARG_TOOLS)

-ag, --agent, -no-ag, --no-agent

whether to enable CORS proxy and all built-in tools - do not enable in untrusted environments (default: disabled) note: for security reasons, this will limit --cors-origins to localhost by default (env: LLAMA_ARG_AGENT)

--ui, --webui, --no-ui, --no-webui

whether to enable the Web UI (default: enabled) (env: LLAMA_ARG_UI)

--embedding, --embeddings

restrict to only support embedding use case; use only with dedicated embedding models (default: disabled) (env: LLAMA_ARG_EMBEDDINGS)

--rerank, --reranking

enable reranking endpoint on server (default: disabled) (env: LLAMA_ARG_RERANKING)

--api-key KEY

API key to use for authentication, multiple keys can be provided as a comma-separated list (default: none) (env: LLAMA_API_KEY)

--api-key-file FNAME

path to file containing API keys, one per line; lines starting with a hash are treated as comments (default: none) (env: LLAMA_ARG_API_KEY_FILE)

--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, must be a valid json object string, e.g. '{"key1":"value1","key2":"value2"}' (env: LLAMA_ARG_CHAT_TEMPLATE_KWARGS)

-to, --timeout N

server read/write timeout in seconds (default: 3600) (env: LLAMA_ARG_TIMEOUT)

--sse-ping-interval N

server SSE ping interval in seconds (-1 = disabled, default: 30) (env: LLAMA_ARG_SSE_PING_INTERVAL)

--threads-http N

number of threads used to process HTTP requests (default: -1) (env: LLAMA_ARG_THREADS_HTTP)

--cache-prompt, --no-cache-prompt

whether to enable prompt caching (default: enabled) (env: LLAMA_ARG_CACHE_PROMPT)

--cache-reuse N

min chunk size to attempt reusing from the cache via KV shifting, requires prompt caching to be enabled (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)

--props

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

--slots, --no-slots

expose slots monitoring endpoint (default: enabled) (env: LLAMA_ARG_ENDPOINT_SLOTS)

--slot-save-path PATH

path to save slot kv cache (default: disabled)

--media-path PATH

directory for loading local media files; files can be accessed via file: // URLs using relative paths (default: disabled)

--models-dir PATH

directory containing models for the router server (default: disabled) (env: LLAMA_ARG_MODELS_DIR)

--models-preset PATH

path to INI file containing model presets for the router server (default: disabled) (env: LLAMA_ARG_MODELS_PRESET)

--models-max N

for router server, maximum number of models to load simultaneously (default: 4, 0 = unlimited) (env: LLAMA_ARG_MODELS_MAX)

--models-autoload, --no-models-autoload

for router server, whether to automatically load models (default:

enabled) (env: LLAMA_ARG_MODELS_AUTOLOAD)

--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)

-rea, --reasoning [on|off|auto]

Use reasoning/thinking in the chat ('on', 'off', or 'auto', default: 'auto' (detect from template)) (env: LLAMA_ARG_REASONING)

--reasoning-budget N

token budget for thinking: -1 for unrestricted, 0 for immediate end, N>0 for token budget (default: -1) (env: LLAMA_ARG_THINK_BUDGET)

--reasoning-budget-message MESSAGE

message injected before the end-of-thinking tag when reasoning budget is exhausted (default: none) (env: LLAMA_ARG_THINK_BUDGET_MESSAGE)

--reasoning-preserve, --no-reasoning-preserve

preserve reasoning trace in the full history, not just the last

assistant message (default: template default) compatible with certain templates having 'supports_preserve_reasoning' capability example: https://docs.z.ai/guides/capabilities/thinking-mode#preserved-thinking (env: LLAMA_ARG_REASONING_PRESERVE)

--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, deepseek-ocr, deepseek2, deepseek3, exaone-moe, exaone3, exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite, granite-4.0, granite-4.1, grok-2, hunyuan-dense, hunyuan-moe, hunyuan-vl, 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, deepseek-ocr, deepseek2, deepseek3, exaone-moe, exaone3, exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite, granite-4.0, granite-4.1, grok-2, hunyuan-dense, hunyuan-moe, hunyuan-vl, 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)

--skip-chat-parsing, --no-skip-chat-parsing

force a pure content parser, even if a Jinja template is specified;

model will output everything in the content section, including any reasoning and/or tool calls (default: disabled) (env: LLAMA_ARG_SKIP_CHAT_PARSING)

--prefill-assistant, --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_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: 0.10, 0.0 = disabled)

--lora-init-without-apply

load LoRA adapters without applying them (apply later via POST /lora-adapters) (default: disabled)

--sleep-idle-seconds SECONDS

number of seconds of idleness after which the server will sleep (default: -1; -1 = disabled)

--log-prompts-dir PATH

Log prompts to directory (auto-created if not present; only used for debugging, default: disabled)

-mv, --model-vocoder FNAME

vocoder model for audio generation (default: unused)

--tts-use-guide-tokens

Use guide tokens to improve TTS word recall

--embd-gemma-default

use default EmbeddingGemma 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)

--fim-qwen-30b-default

use default Qwen 3 Coder 30B A3B Instruct (note: can download weights from the internet)

--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)

--spec-default

enable default speculative decoding config