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LLAMA-SPECULATIVE-SIMPLE(1) User Commands LLAMA-SPECULATIVE-SIMPLE(1)

NAME

llama-speculative-simple - llama-speculative-simple

DESCRIPTION

load_backend: loaded CPU backend from /usr/lib/x86_64-linux-gnu/ggml/backends0/libggml-cpu-icelake.so ----- common params -----

-h, --help, --usage print usage and exit --version show version and build info --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 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: 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)

-p, --prompt PROMPT prompt to start generation with; for system message, use -sys --no-perf disable internal libllama performance timings (default: false)

(env: LLAMA_ARG_NO_PERF)

-f, --file FNAME a file containing the prompt (default: none) -bf, --binary-file FNAME binary file containing the prompt (default: none) -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

(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

(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

(env: LLAMA_ARG_YARN_ORIG_CTX)

--yarn-ext-factor N YaRN: extrapolation mix factor (default: -1.0, 0.0 = full

(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

(default: f16) (env: LLAMA_ARG_CACHE_TYPE_K)

-ctv, --cache-type-v TYPE KV cache data type for V

(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

(env: LLAMA_ARG_NO_MMAP)

--numa TYPE attempt optimizations that help on some NUMA systems

- 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

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:

- 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

(env: LLAMA_ARG_TENSOR_SPLIT)

-mg, --main-gpu INDEX the GPU to use for the model (with split-mode = none), or for

(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

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

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`

(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]

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]

(env: LLAMA_ARG_HFD_REPO)

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

(env: LLAMA_ARG_HF_FILE)

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

(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

(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

(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

(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

(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

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.

(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,

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 -----

-co, --color colorise output to distinguish prompt and user input from generations

(default: false)

-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)

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

same as --cpu-mask)

-Crd, --cpu-range-draft lo-hi Ranges of CPUs for affinity. Complements --cpu-mask-draft --cpu-strict-draft <0|1> Use strict CPU placement for draft model (default: same as

--cpu-strict)

--prio-draft N set draft process/thread priority : 0-normal, 1-medium, 2-high,

3-realtime (default: 0)

--poll-draft <0|1> Use polling to wait for draft model work (default: same as --poll]) -Cbd, --cpu-mask-batch-draft M Draft model CPU affinity mask. Complements cpu-range-draft (default:

same as --cpu-mask)

-Crbd, --cpu-range-batch-draft lo-hi Ranges of CPUs for affinity. Complements --cpu-mask-draft-batch) --cpu-strict-batch-draft <0|1> Use strict CPU placement for draft model (default: --cpu-strict-draft) --prio-batch-draft N set draft process/thread priority : 0-normal, 1-medium, 2-high,

3-realtime (default: 0)

--poll-batch-draft <0|1> Use polling to wait for draft model work (default: --poll-draft) --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-split P speculative decoding split probability (default: 0.1)

(env: LLAMA_ARG_DRAFT_P_SPLIT)

--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

(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

(env: LLAMA_ARG_N_GPU_LAYERS_DRAFT)

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

(env: LLAMA_ARG_MODEL_DRAFT)
August 2025 debian