bdi_podman_serverconf/Services/llamacpp-swap/DOCS.md

----- 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 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: 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) (env: LLAMA_ARG_SWA_FULL) --kv-unified, -kvu use single unified KV buffer for the KV cache of all sequences (default: false) (more info) (env: LLAMA_ARG_KV_SPLIT) -fa, --flash-attn [on|off|auto] set Flash Attention use ('on', 'off', or 'auto', default: 'auto') (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: -1.0) (env: LLAMA_ARG_YARN_BETA_FAST) -nkvo, --no-kv-offload disable KV offload (env: LLAMA_ARG_NO_KV_OFFLOAD) -nr, --no-repack disable weight repacking (env: LLAMA_ARG_NO_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) --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 =,... override tensor buffer type --cpu-moe, -cmoe keep all Mixture of Experts (MoE) weights in the CPU (env: LLAMA_ARG_CPU_MOE) --n-cpu-moe, -ncmoe 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 (default: -1) (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) -dr, --docker-repo [/][: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 /[: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 /[: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 /[: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 [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. (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) --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 -----

--ctx-checkpoints, --swa-checkpoints N max number of context checkpoints to create per slot (default: 8) (more info) (env: LLAMA_ARG_CTX_CHECKPOINTS) --cache-ram, -cram N set the maximum cache size in MiB (default: 8192, -1 - no limit, 0 - disable) (more info) (env: LLAMA_ARG_CACHE_RAM) --no-context-shift disables context shift on infinite text generation (default: enabled) (env: LLAMA_ARG_NO_CONTEXT_SHIFT) --context-shift enables 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) --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) --override-tensor-draft, -otd =,... override tensor buffer type for draft model --cpu-moe-draft, -cmoed keep all Mixture of Experts (MoE) weights in the CPU for the draft model (env: LLAMA_ARG_CPU_MOE_DRAFT) --n-cpu-moe-draft, -ncmoed 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 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: ) (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) (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 enable slots monitoring endpoint (default: enabled) (env: LLAMA_ARG_ENDPOINT_SLOTS) --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 - deepseek-legacy: keeps <think> tags in message.content while also populating message.reasoning_content (default: auto) (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, bailing-think, bailing2, chatglm3, chatglm4, chatml, command-r, deepseek, deepseek2, deepseek3, 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, phi3, phi4, rwkv-world, seed_oss, 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, bailing-think, bailing2, chatglm3, chatglm4, chatml, command-r, deepseek, deepseek2, deepseek3, 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, phi3, phi4, rwkv-world, seed_oss, 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: 0.10, 0.0 = disabled) --lora-init-without-apply load LoRA adapters without applying them (apply later via POST /lora-adapters) (default: 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-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) --spec-replace TARGET DRAFT translate the string in TARGET into DRAFT if the draft model and main model are not compatible -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)