manpages

llama-server(1)

LLAMA-SERVER(1) User Commands LLAMA-SERVER(1)

NAME

llama-server - manual page for llama-server 8470 (db9d8aa4 [alt1])

DESCRIPTION

Common Params:

-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)](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}
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: ggml-org/GLM-4.7-Flash-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:

--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)

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)
-cpent, --checkpoint-every-n-tokens N
create a checkpoint every n tokens during prefill (processing), -1 to disable (default: 8192) (env: LLAMA_ARG_CHECKPOINT_EVERY_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)
--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)

-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)
-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)
--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: ) (env: LLAMA_ARG_STATIC_PATH)
--api-prefix PREFIX
prefix path the server serves from, without the trailing slash (default: ) (env: LLAMA_ARG_API_PREFIX)
--webui-config JSON
JSON that provides default WebUI settings (overrides WebUI defaults) (env: LLAMA_ARG_WEBUI_CONFIG)
--webui-config-file PATH
JSON file that provides default WebUI settings (overrides WebUI defaults) (env: LLAMA_ARG_WEBUI_CONFIG_FILE)

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

experimental:
whether to enable MCP CORS proxy - do not enable in
untrusted environments (default:
disabled)
(env:
LLAMA_ARG_WEBUI_MCP_PROXY)
--webui, --no-webui
whether to enable the Web UI (default: enabled) (env: LLAMA_ARG_WEBUI)
--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 (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, must be a valid json object string, e.g. '{"key1":"value1","key2":"value2"}' (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-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)
--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)

--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)
-td, --threads-draft N
number of threads to use during generation (default: same as --threads)
-tbd, --threads-batch-draft N
number of threads to use during batch and prompt processing (default: same as --threads-draft)
--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

--spec-type [none|ngram-cache|ngram-simple|ngram-map-k|ngram-map-k4v|ngram-mod]

type of speculative decoding to use when no draft model is provided
(default: none)
(env:
LLAMA_ARG_SPEC_TYPE)
--spec-ngram-size-n N
ngram size N for ngram-simple/ngram-map speculative decoding, length of lookup n-gram (default: 12)
--spec-ngram-size-m N
ngram size M for ngram-simple/ngram-map speculative decoding, length of draft m-gram (default: 48)
--spec-ngram-min-hits N
minimum hits for ngram-map speculative decoding (default: 1)
-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)
March 2026 llama-server 8470 (db9d8aa4 [alt1])