-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)

-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: -1.0, 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: -1.0)

(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 disabled, slower load but may reduce

pageouts if not using mlock) (default: enabled)

(env: LLAMA_ARG_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 -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 MiB target margin per device for --fit option, 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 or repeat this argument.

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

--op-offload, --no-op-offload whether to offload host tensor operations to device (default: true) --lora FNAME path to LoRA adapter (use comma-separated values to load multiple

adapters)

--lora-scaled FNAME:SCALE,... path to LoRA adapter with user defined scaling (format:¶

FNAME:SCALE,...)

note: use comma-separated values

--control-vector FNAME add a control vector

note: use comma-separated values to add multiple control vectors

--control-vector-scaled FNAME:SCALE,...

add a control vector with user defined scaling SCALE

note: use comma-separated values (format: FNAME:SCALE,...)

--control-vector-layer-range START END

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

-m, --model FNAME model path to load

(env: LLAMA_ARG_MODEL)

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

(env: LLAMA_ARG_MODEL_URL)

-dr, --docker-repo [<repo>/]<model>[:quant]

Docker Hub model repository. repo is optional, default to ai/. quant

is optional, default to :latest. example: gemma3 (default: unused) (env: LLAMA_ARG_DOCKER_REPO)

-hf, -hfr, --hf-repo <user>/<model>[:quant]

Hugging Face model repository; quant is optional, case-insensitive,

default to Q4_K_M, or falls back to the first file in the repo if Q4_K_M doesn't exist. mmproj is also downloaded automatically if available. to disable, add --no-mmproj example: unsloth/phi-4-GGUF:q4_k_m (default: unused) (env: LLAMA_ARG_HF_REPO)

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

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

(env: LLAMA_ARG_HFD_REPO)

-hff, --hf-file FILE Hugging Face model file. If specified, it will override the quant in

--hf-repo (default: unused)

(env: LLAMA_ARG_HF_FILE)

-hfv, -hfrv, --hf-repo-v <user>/<model>[:quant]

Hugging Face model repository for the vocoder model (default: unused)

(env: LLAMA_ARG_HF_REPO_V)

-hffv, --hf-file-v FILE Hugging Face model file for the vocoder model (default: unused)

(env: LLAMA_ARG_HF_FILE_V)

-hft, --hf-token TOKEN Hugging Face access token (default: value from HF_TOKEN environment

variable)

(env: HF_TOKEN)

--log-disable Log disable --log-file FNAME Log to file

(env: LLAMA_LOG_FILE)

--log-colors [on|off|auto] Set colored logging ('on', 'off', or 'auto', default: 'auto')

'auto' enables colors when output is to a terminal

(env: LLAMA_LOG_COLORS)

-v, --verbose, --log-verbose Set verbosity level to infinity (i.e. log all messages, useful for

debugging)

--offline Offline mode: forces use of cache, prevents network access

(env: LLAMA_OFFLINE)

-lv, --verbosity, --log-verbosity N Set the verbosity threshold. Messages with a higher verbosity will be

ignored. Values:

- 0: generic output - 1: error - 2: warning - 3: info - 4: debug

(default: 3)

(env: LLAMA_LOG_VERBOSITY)

--log-prefix Enable prefix in log messages

(env: LLAMA_LOG_PREFIX)

--log-timestamps Enable timestamps in log messages

(env: LLAMA_LOG_TIMESTAMPS)

-ctkd, --cache-type-k-draft TYPE KV cache data type for K for the draft model

allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1

(default: f16) (env: LLAMA_ARG_CACHE_TYPE_K_DRAFT)

-ctvd, --cache-type-v-draft TYPE KV cache data type for V for the draft model

allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1

(default: f16) (env: LLAMA_ARG_CACHE_TYPE_V_DRAFT)

----- sampling params -----

--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 N temperature (default: 0.8) --top-k N top-k sampling (default: 40, 0 = disabled)

(env: LLAMA_ARG_TOP_K)

--top-p N top-p sampling (default: 0.9, 1.0 = disabled) --min-p N min-p sampling (default: 0.1, 0.0 = disabled) --top-nsigma N top-n-sigma sampling (default: -1.0, -1.0 = 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 -----

--chunks N max number of chunks to process (default: -1, -1 = all) --warmup, --no-warmup whether to perform warmup with an empty run (default: enabled) --pooling {none,mean,cls,last,rank} pooling type for embeddings, use model default if unspecified

(env: LLAMA_ARG_POOLING)

--context-file FNAME file to load context from (use comma-separated values to specify

multiple files)

--chunk-size N minimum length of embedded text chunks (default: 64) --chunk-separator STRING separator between chunks (default: '

')

example usage:

obj-x86_64-linux-gnu/bin/llama-retrieval --model ./models/bge-base-en-v1.5-f16.gguf --top-k 3 --context-file README.md --context-file License --chunk-size 100 --chunk-separator .