diff --git a/reference/llama-server-settings.md b/reference/llama-server-settings.md
new file mode 100644
index 0000000..03dca25
--- /dev/null
+++ b/reference/llama-server-settings.md
@@ -0,0 +1,930 @@
+---
+created: '2026-04-10T01:19:06+00:00'
+id: c693060b-7794-4d1c-995d-53b6c951352c
+keywords:
+- llama-server
+- llama.cpp
+- HTTP server
+- GGUF
+- OpenAI API
+- Anthropic API
+- inference
+- completion
+- chat completions
+- embeddings
+- reranking
+- speculative decoding
+- continuous batching
+- KV cache
+- sampling
+- router mode
+- multimodal
+- LoRA
+- function calling
+links: []
+modified: '2026-04-10T01:19:06+00:00'
+summary: Comprehensive reference for llama-server (LLaMA.cpp HTTP Server) covering
+  all command-line parameters (common, sampling, server-specific), API endpoints (native
+  and OpenAI/Anthropic-compatible), router mode for multi-model serving, build instructions,
+  and usage examples.
+tags:
+- reference
+- llama-cpp
+- llama-server
+- inference-server
+- api
+- openai-compatible
+title: LLaMA.cpp HTTP Server (llama-server) — Settings & API Reference
+---
+
+# LLaMA.cpp HTTP Server (llama-server)
+
+Fast, lightweight, pure C/C++ HTTP server based on [httplib](https://github.com/yhirose/cpp-httplib), [nlohmann::json](https://github.com/nlohmann/json) and **llama.cpp**.
+
+Set of LLM REST APIs and a web UI to interact with llama.cpp.
+
+**Features:**
+- LLM inference of F16 and quantized models on GPU and CPU
+- [OpenAI API](https://github.com/openai/openai-openapi) compatible chat completions, responses, and embeddings routes
+- [Anthropic Messages API](https://docs.anthropic.com/en/api/messages) compatible chat completions
+- Reranking endpoint (https://github.com/ggml-org/llama.cpp/pull/9510)
+- Parallel decoding with multi-user support
+- Continuous batching
+- Multimodal ([documentation](../../docs/multimodal.md)) / with OpenAI-compatible API support
+- Monitoring endpoints
+- Schema-constrained JSON response format
+- Prefilling of assistant messages similar to the Claude API
+- [Function calling](../../docs/function-calling.md) / tool use for ~any model
+- Speculative decoding
+- Easy-to-use web UI
+
+For the full list of features, please refer to [server's changelog](https://github.com/ggml-org/llama.cpp/issues/9291)
+
+## Usage
+
+### Common params
+
+| Argument | Explanation |
+| -------- | ----------- |
+| `-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 |
+| `-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) (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: 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: 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`) |
+| `--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. Options: distribute, isolate, numactl (env: `LLAMA_ARG_NUMA`) |
+| `-dev, --device <dev1,dev2,..>` | comma-separated list of devices to use for offloading (none = don't offload) (env: `LLAMA_ARG_DEVICE`) |
+| `--list-devices` | print list of available devices and exit |
+| `-ot, --override-tensor <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 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: exact number, 'auto', or 'all' (default: auto) (env: `LLAMA_ARG_N_GPU_LAYERS`) |
+| `-sm, --split-mode {none,layer,row}` | how to split model across multiple GPUs (default: layer) (env: `LLAMA_ARG_SPLIT_MODE`) |
+| `-ts, --tensor-split N0,N1,N2,...` | fraction of model to offload to each GPU, comma-separated proportions (env: `LLAMA_ARG_TENSOR_SPLIT`) |
+| `-mg, --main-gpu INDEX` | GPU to use for model or intermediate results (default: 0) (env: `LLAMA_ARG_MAIN_GPU`) |
+| `-fit, --fit [on\|off]` | whether to adjust unset arguments to fit in device memory (default: 'on') (env: `LLAMA_ARG_FIT`) |
+| `-fitt, --fit-target MiB0,MiB1,...` | target margin per device for --fit, comma-separated (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,...` | override model metadata by key. Types: int, float, bool, str |
+| `--op-offload, --no-op-offload` | whether to offload host tensor operations to device (default: true) |
+| `--lora FNAME` | path to LoRA adapter (comma-separated for multiple) |
+| `--lora-scaled FNAME:SCALE,...` | path to LoRA adapter with user defined scaling |
+| `--control-vector FNAME` | add a control vector (comma-separated for multiple) |
+| `--control-vector-scaled FNAME:SCALE,...` | add a control vector with user defined scaling |
+| `--control-vector-layer-range START END` | layer range to apply the control vector(s) to |
+| `-m, --model FNAME` | model path to load (env: `LLAMA_ARG_MODEL`) |
+| `-mu, --model-url MODEL_URL` | model download url (env: `LLAMA_ARG_MODEL_URL`) |
+| `-dr, --docker-repo [<repo>/]<model>[:quant]` | Docker Hub model repository (env: `LLAMA_ARG_DOCKER_REPO`) |
+| `-hf, -hfr, --hf-repo <user>/<model>[:quant]` | Hugging Face model repository (env: `LLAMA_ARG_HF_REPO`) |
+| `-hfd, -hfrd, --hf-repo-draft <user>/<model>[:quant]` | Same as --hf-repo, but for the draft model (env: `LLAMA_ARG_HFD_REPO`) |
+| `-hff, --hf-file FILE` | Hugging Face model file, overrides quant in --hf-repo (env: `LLAMA_ARG_HF_FILE`) |
+| `-hfv, -hfrv, --hf-repo-v <user>/<model>[:quant]` | Hugging Face model repository for vocoder model (env: `LLAMA_ARG_HF_REPO_V`) |
+| `-hffv, --hf-file-v FILE` | Hugging Face model file for vocoder model (env: `LLAMA_ARG_HF_FILE_V`) |
+| `-hft, --hf-token TOKEN` | Hugging Face access token (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 (default: 'auto') (env: `LLAMA_LOG_COLORS`) |
+| `-v, --verbose, --log-verbose` | Set verbosity level to infinity |
+| `--offline` | Offline mode: forces use of cache, prevents network access (env: `LLAMA_OFFLINE`) |
+| `-lv, --verbosity, --log-verbosity N` | Set verbosity threshold. 0=generic, 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 (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
+
+| Argument | Explanation |
+| -------- | ----------- |
+| `--samplers SAMPLERS` | samplers used for generation, 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 (default: edskypmxt) |
+| `--ignore-eos` | ignore end of stream token and continue generating |
+| `--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` | DRY sampling multiplier (default: 0.00, 0.0 = disabled) |
+| `--dry-base N` | DRY sampling base value (default: 1.75) |
+| `--dry-allowed-length N` | allowed length for DRY sampling (default: 2) |
+| `--dry-penalty-last-n N` | DRY penalty for the last n tokens (default: -1, 0 = disable, -1 = context size) |
+| `--dry-sequence-breaker STRING` | add sequence breaker for DRY sampling; use "none" for no breakers |
+| `--adaptive-target N` | adaptive-p: select tokens near this probability (default: -1.00, disabled) |
+| `--adaptive-decay N` | adaptive-p: decay rate for target adaptation (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 (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 |
+| `--grammar GRAMMAR` | BNF-like grammar to constrain generations |
+| `--grammar-file FNAME` | file to read grammar from |
+| `-j, --json-schema SCHEMA` | JSON schema to constrain generations |
+| `-jf, --json-schema-file FILE` | File containing a JSON schema to constrain generations |
+| `-bs, --backend-sampling` | enable backend sampling (experimental) (env: `LLAMA_ARG_BACKEND_SAMPLING`) |
+
+### Server-specific params
+
+| Argument | Explanation |
+| -------- | ----------- |
+| `-lcs, --lookup-cache-static FNAME` | path to static lookup cache for lookup decoding |
+| `-lcd, --lookup-cache-dynamic FNAME` | path to dynamic lookup cache for lookup decoding |
+| `-ctxcp, --ctx-checkpoints, --swa-checkpoints N` | max context checkpoints per slot (default: 32) (env: `LLAMA_ARG_CTX_CHECKPOINTS`) |
+| `-cpent, --checkpoint-every-n-tokens N` | checkpoint every n tokens during prefill (default: 8192) (env: `LLAMA_ARG_CHECKPOINT_EVERY_NT`) |
+| `-cram, --cache-ram N` | maximum cache size in MiB (default: 8192, -1 = no limit, 0 = disable) (env: `LLAMA_ARG_CACHE_RAM`) |
+| `-kvu, --kv-unified, -no-kvu, --no-kv-unified` | single unified KV buffer shared across all sequences (env: `LLAMA_ARG_KV_UNIFIED`) |
+| `--clear-idle, --no-clear-idle` | save and clear idle slots on new task (default: enabled) (env: `LLAMA_ARG_CLEAR_IDLE`) |
+| `--context-shift, --no-context-shift` | context shift on infinite text generation (default: disabled) (env: `LLAMA_ARG_CONTEXT_SHIFT`) |
+| `-r, --reverse-prompt PROMPT` | halt generation at PROMPT |
+| `-sp, --special` | special tokens output enabled (default: false) |
+| `--warmup, --no-warmup` | perform warmup with empty run (default: enabled) |
+| `--spm-infill` | use Suffix/Prefix/Middle pattern for infill (default: disabled) |
+| `--pooling {none,mean,cls,last,rank}` | pooling type for embeddings (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` | continuous batching / dynamic batching (default: enabled) (env: `LLAMA_ARG_CONT_BATCHING`) |
+| `-mm, --mmproj FILE` | path to multimodal projector file (env: `LLAMA_ARG_MMPROJ`) |
+| `-mmu, --mmproj-url URL` | URL to multimodal projector file (env: `LLAMA_ARG_MMPROJ_URL`) |
+| `--mmproj-auto, --no-mmproj, --no-mmproj-auto` | auto-detect multimodal projector (default: enabled) (env: `LLAMA_ARG_MMPROJ_AUTO`) |
+| `--mmproj-offload, --no-mmproj-offload` | GPU offloading for multimodal projector (default: enabled) (env: `LLAMA_ARG_MMPROJ_OFFLOAD`) |
+| `--image-min-tokens N` | minimum tokens per image for vision models with dynamic resolution (env: `LLAMA_ARG_IMAGE_MIN_TOKENS`) |
+| `--image-max-tokens N` | maximum tokens per image for vision models with dynamic resolution (env: `LLAMA_ARG_IMAGE_MAX_TOKENS`) |
+| `-otd, --override-tensor-draft <pattern>=<buffer type>,...` | override tensor buffer type for draft model |
+| `-cmoed, --cpu-moe-draft` | keep all MoE weights in CPU for draft model (env: `LLAMA_ARG_CPU_MOE_DRAFT`) |
+| `-ncmoed, --n-cpu-moe-draft N` | keep MoE weights of first N layers in CPU for draft model (env: `LLAMA_ARG_N_CPU_MOE_DRAFT`) |
+| `-a, --alias STRING` | model name aliases, comma-separated (env: `LLAMA_ARG_ALIAS`) |
+| `--tags STRING` | model tags, comma-separated (env: `LLAMA_ARG_TAGS`) |
+| `--host HOST` | ip address to listen, or UNIX socket if 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 same port (env: `LLAMA_ARG_REUSE_PORT`) |
+| `--path PATH` | path to serve static files from (env: `LLAMA_ARG_STATIC_PATH`) |
+| `--api-prefix PREFIX` | prefix path the server serves from (env: `LLAMA_ARG_API_PREFIX`) |
+| `--webui-config JSON` | JSON for default WebUI settings (env: `LLAMA_ARG_WEBUI_CONFIG`) |
+| `--webui-config-file PATH` | JSON file for default WebUI settings (env: `LLAMA_ARG_WEBUI_CONFIG_FILE`) |
+| `--webui-mcp-proxy, --no-webui-mcp-proxy` | enable MCP CORS proxy - experimental, do not enable in untrusted environments (env: `LLAMA_ARG_WEBUI_MCP_PROXY`) |
+| `--tools TOOL1,TOOL2,...` | enable built-in tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, apply_diff (env: `LLAMA_ARG_TOOLS`) |
+| `--webui, --no-webui` | enable the Web UI (default: enabled) (env: `LLAMA_ARG_WEBUI`) |
+| `--embedding, --embeddings` | restrict to embedding use case only (env: `LLAMA_ARG_EMBEDDINGS`) |
+| `--rerank, --reranking` | enable reranking endpoint (env: `LLAMA_ARG_RERANKING`) |
+| `--api-key KEY` | API key(s) for authentication, comma-separated (env: `LLAMA_API_KEY`) |
+| `--api-key-file FNAME` | path to file containing API keys |
+| `--ssl-key-file FNAME` | PEM-encoded SSL private key (env: `LLAMA_ARG_SSL_KEY_FILE`) |
+| `--ssl-cert-file FNAME` | PEM-encoded SSL certificate (env: `LLAMA_ARG_SSL_CERT_FILE`) |
+| `--chat-template-kwargs STRING` | additional params for 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` | threads for HTTP request processing (default: -1) (env: `LLAMA_ARG_THREADS_HTTP`) |
+| `--cache-prompt, --no-cache-prompt` | prompt caching (default: enabled) (env: `LLAMA_ARG_CACHE_PROMPT`) |
+| `--cache-reuse N` | min chunk size for KV shifting cache reuse (default: 0) (env: `LLAMA_ARG_CACHE_REUSE`) |
+| `--metrics` | enable prometheus compatible metrics endpoint (env: `LLAMA_ARG_ENDPOINT_METRICS`) |
+| `--props` | enable changing global properties via POST /props (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 |
+| `--media-path PATH` | directory for loading local media files |
+| `--models-dir PATH` | directory containing models for router server (env: `LLAMA_ARG_MODELS_DIR`) |
+| `--models-preset PATH` | path to INI file containing model presets (env: `LLAMA_ARG_MODELS_PRESET`) |
+| `--models-max N` | max models to load simultaneously in router (default: 4, 0 = unlimited) (env: `LLAMA_ARG_MODELS_MAX`) |
+| `--models-autoload, --no-models-autoload` | auto-load models in router mode (default: enabled) (env: `LLAMA_ARG_MODELS_AUTOLOAD`) |
+| `--jinja, --no-jinja` | use jinja template engine for chat (default: enabled) (env: `LLAMA_ARG_JINJA`) |
+| `--reasoning-format FORMAT` | thought tag handling: none, deepseek, deepseek-legacy (default: auto) (env: `LLAMA_ARG_THINK`) |
+| `-rea, --reasoning [on\|off\|auto]` | reasoning/thinking in chat (default: auto) (env: `LLAMA_ARG_REASONING`) |
+| `--reasoning-budget N` | token budget for thinking: -1 unrestricted, 0 immediate end, N>0 budget (default: -1) (env: `LLAMA_ARG_THINK_BUDGET`) |
+| `--reasoning-budget-message MESSAGE` | message injected when reasoning budget exhausted (env: `LLAMA_ARG_THINK_BUDGET_MESSAGE`) |
+| `--chat-template JINJA_TEMPLATE` | custom jinja chat template or built-in name (env: `LLAMA_ARG_CHAT_TEMPLATE`) |
+| `--chat-template-file JINJA_TEMPLATE_FILE` | custom jinja chat template file (env: `LLAMA_ARG_CHAT_TEMPLATE_FILE`) |
+| `--skip-chat-parsing, --no-skip-chat-parsing` | force pure content parser (env: `LLAMA_ARG_SKIP_CHAT_PARSING`) |
+| `--prefill-assistant, --no-prefill-assistant` | prefill assistant response (default: enabled) (env: `LLAMA_ARG_PREFILL_ASSISTANT`) |
+| `-sps, --slot-prompt-similarity SIMILARITY` | prompt similarity threshold for slot reuse (default: 0.10) |
+| `--lora-init-without-apply` | load LoRA adapters without applying |
+| `--sleep-idle-seconds SECONDS` | seconds of idleness before server sleeps (default: -1, disabled) |
+| `-td, --threads-draft N` | threads for draft model generation |
+| `-tbd, --threads-batch-draft N` | threads for draft model batch processing |
+| `--draft, --draft-n, --draft-max N` | tokens to draft for speculative decoding (default: 16) (env: `LLAMA_ARG_DRAFT_MAX`) |
+| `--draft-min, --draft-n-min N` | minimum draft tokens for speculative decoding (default: 0) (env: `LLAMA_ARG_DRAFT_MIN`) |
+| `--draft-p-min P` | minimum speculative decoding probability (default: 0.75) (env: `LLAMA_ARG_DRAFT_P_MIN`) |
+| `-cd, --ctx-size-draft N` | prompt context size for draft model (env: `LLAMA_ARG_CTX_SIZE_DRAFT`) |
+| `-devd, --device-draft <dev1,dev2,..>` | devices for draft model offloading |
+| `-ngld, --gpu-layers-draft N` | draft model GPU layers (default: auto) (env: `LLAMA_ARG_N_GPU_LAYERS_DRAFT`) |
+| `-md, --model-draft FNAME` | draft model for speculative decoding (env: `LLAMA_ARG_MODEL_DRAFT`) |
+| `--spec-replace TARGET DRAFT` | translate strings between main and draft model |
+| `--spec-type [none\|ngram-cache\|ngram-simple\|ngram-map-k\|ngram-map-k4v\|ngram-mod]` | speculative decoding type without draft model (env: `LLAMA_ARG_SPEC_TYPE`) |
+| `--spec-ngram-size-n N` | ngram size N for ngram speculative decoding (default: 12) |
+| `--spec-ngram-size-m N` | ngram size M for ngram speculative decoding (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 |
+| `--tts-use-guide-tokens` | Use guide tokens to improve TTS word recall |
+| `--embd-gemma-default` | use default EmbeddingGemma model |
+| `--fim-qwen-1.5b-default` | use default Qwen 2.5 Coder 1.5B |
+| `--fim-qwen-3b-default` | use default Qwen 2.5 Coder 3B |
+| `--fim-qwen-7b-default` | use default Qwen 2.5 Coder 7B |
+| `--fim-qwen-7b-spec` | use Qwen 2.5 Coder 7B + 0.5B draft |
+| `--fim-qwen-14b-spec` | use Qwen 2.5 Coder 14B + 0.5B draft |
+| `--fim-qwen-30b-default` | use default Qwen 3 Coder 30B A3B Instruct |
+| `--gpt-oss-20b-default` | use gpt-oss-20b |
+| `--gpt-oss-120b-default` | use gpt-oss-120b |
+| `--vision-gemma-4b-default` | use Gemma 3 4B QAT |
+| `--vision-gemma-12b-default` | use Gemma 3 12B QAT |
+
+## Environment Variables
+
+If both command line argument and environment variable are set for the same param, the argument takes precedence.
+
+For boolean options like `--mmap` or `--kv-offload`, environment variable handling:
+- `LLAMA_ARG_MMAP=true` / `1` / `on` / `enabled` → enabled
+- `LLAMA_ARG_MMAP=false` / `0` / `off` / `disabled` → disabled
+- Presence of `LLAMA_ARG_NO_MMAP` → disabled
+
+### Docker Compose Example
+
+```yml
+services:
+  llamacpp-server:
+    image: ghcr.io/ggml-org/llama.cpp:server
+    ports:
+      - 8080:8080
+    volumes:
+      - ./models:/models
+    environment:
+      LLAMA_ARG_MODEL: /models/my_model.gguf
+      LLAMA_ARG_CTX_SIZE: 4096
+      LLAMA_ARG_N_PARALLEL: 2
+      LLAMA_ARG_ENDPOINT_METRICS: 1
+      LLAMA_ARG_PORT: 8080
+```
+
+## Multimodal Support
+
+Multimodal support is currently an experimental feature. Available in:
+- OAI-compatible chat endpoint
+- Non-OAI-compatible completions endpoint
+- Non-OAI-compatible embeddings endpoint
+
+The multimodal projector is auto-detected when using `-hf`. Use `--no-mmproj` to disable.
+
+## Built-in Tools
+
+Built-in tools enable the LLM to access the local file system from the Web UI. Start with `--tools all` or specify individual tools: `--tools read_file,file_glob_search,...`.
+
+Available tools: `read_file`, `file_glob_search`, `grep_search`, `exec_shell_command`, `write_file`, `edit_file`, `apply_diff`
+
+> ⚠️ Do not enable in untrusted environments.
+
+## Build
+
+### Standard Build
+
+```bash
+cmake -B build
+cmake --build build --config Release -t llama-server
+```
+
+Binary: `./build/bin/llama-server`
+
+### Build with SSL (OpenSSL 3)
+
+```bash
+cmake -B build -DLLAMA_OPENSSL=ON
+cmake --build build --config Release -t llama-server
+```
+
+## Quick Start
+
+### Unix (Linux, macOS)
+
+```bash
+./llama-server -m models/7B/ggml-model.gguf -c 2048
+```
+
+### Windows
+
+```powershell
+llama-server.exe -m models\7B\ggml-model.gguf -c 2048
+```
+
+Listens on `127.0.0.1:8080` by default.
+
+### Docker
+
+```bash
+docker run -p 8080:8080 -v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:server -m models/7B/ggml-model.gguf -c 512 --host 0.0.0.0 --port 8080
+
+# With CUDA:
+docker run -p 8080:8080 -v /path/to/models:/models --gpus all ghcr.io/ggml-org/llama.cpp:server-cuda -m models/7B/ggml-model.gguf -c 512 --host 0.0.0.0 --port 8080 --n-gpu-layers 99
+```
+
+## Using with cURL
+
+```sh
+curl --request POST \
+    --url http://localhost:8080/completion \
+    --header "Content-Type: application/json" \
+    --data '{"prompt": "Building a website can be done in 10 simple steps:","n_predict": 128}'
+```
+
+---
+
+## API Endpoints
+
+### GET `/health` — Health Check
+
+Public endpoint (no API key). `/v1/health` also works.
+
+- **503**: `{"error": {"code": 503, "message": "Loading model", "type": "unavailable_error"}}`
+- **200**: `{"status": "ok"}`
+
+---
+
+### POST `/completion` — Text Completion
+
+> ⚠️ Not OAI-compatible. Use `/v1/completions` for OAI clients.
+
+**Request options:**
+
+| Field | Type | Default | Description |
+|-------|------|---------|-------------|
+| `prompt` | string/array/object | required | Prompt as string, token array, mixed, or JSON with multimodal data |
+| `temperature` | float | 0.8 | Randomness of generated text |
+| `dynatemp_range` | float | 0.0 | Dynamic temperature range |
+| `dynatemp_exponent` | float | 1.0 | Dynamic temperature exponent |
+| `top_k` | int | 40 | Limit to K most probable tokens |
+| `top_p` | float | 0.95 | Nucleus sampling threshold |
+| `min_p` | float | 0.05 | Minimum probability relative to most likely token |
+| `n_predict` | int | -1 | Max tokens to predict (-1 = infinity) |
+| `n_indent` | int | 0 | Min line indentation (for code completion) |
+| `n_keep` | int | 0 | Tokens to retain when context exceeded (-1 = all) |
+| `n_cmpl` | int | - | Number of completions per prompt |
+| `n_cache_reuse` | int | 0 | Min chunk size for KV shifting cache reuse |
+| `stream` | bool | false | Stream tokens in real-time via SSE |
+| `stop` | array | [] | Stopping strings (not included in output) |
+| `typical_p` | float | 1.0 | Locally typical sampling parameter |
+| `repeat_penalty` | float | 1.1 | Repetition penalty |
+| `repeat_last_n` | int | 64 | Tokens to consider for repeat penalty |
+| `presence_penalty` | float | 0.0 | Presence penalty |
+| `frequency_penalty` | float | 0.0 | Frequency penalty |
+| `dry_multiplier` | float | 0.0 | DRY repetition penalty multiplier |
+| `dry_base` | float | 1.75 | DRY penalty base |
+| `dry_allowed_length` | int | 2 | DRY allowed repeating length |
+| `dry_penalty_last_n` | int | -1 | Tokens to scan for DRY |
+| `dry_sequence_breakers` | array | ['\n',':','"','*'] | DRY sequence breakers |
+| `xtc_probability` | float | 0.0 | XTC token removal chance |
+| `xtc_threshold` | float | 0.1 | XTC minimum probability threshold |
+| `mirostat` | int | 0 | Mirostat mode (0=off, 1, 2) |
+| `mirostat_tau` | float | 5.0 | Mirostat target entropy |
+| `mirostat_eta` | float | 0.1 | Mirostat learning rate |
+| `grammar` | string | - | BNF grammar for constrained generation |
+| `json_schema` | object | - | JSON schema for constrained generation |
+| `seed` | int | -1 | RNG seed (-1 = random) |
+| `ignore_eos` | bool | false | Ignore EOS token |
+| `logit_bias` | array/object | [] | Modify token likelihoods |
+| `n_probs` | int | 0 | Return top N token probabilities |
+| `min_keep` | int | 0 | Force minimum tokens from samplers |
+| `t_max_predict_ms` | int | 0 | Time limit for prediction phase (ms) |
+| `id_slot` | int | -1 | Assign to specific slot |
+| `cache_prompt` | bool | true | Re-use KV cache from previous request |
+| `return_tokens` | bool | false | Return raw token IDs |
+| `samplers` | array | [dry,top_k,typ_p,top_p,min_p,xtc,temperature] | Sampler order |
+| `timings_per_token` | bool | false | Include speed info per token |
+| `return_progress` | bool | false | Include prompt processing progress in stream mode |
+| `post_sampling_probs` | bool | false | Return probabilities after sampling |
+| `response_fields` | array | - | List of specific response fields to return |
+| `lora` | array | - | Per-request LoRA adapters: `[{"id": 0, "scale": 0.5}]` |
+
+**Prompt input shapes:**
+- Single string: `"string"`
+- Single token sequence: `[12, 34, 56]`
+- Mixed tokens and strings: `[12, 34, "string", 56, 78]`
+- JSON object with multimodal: `{"prompt_string": "string", "multimodal_data": ["base64"]}`
+- Multiple prompts: `["string1", "string2"]`
+
+**Response format:**
+
+```json
+{
+  "content": "<generated text>",
+  "tokens": [],
+  "stop": true,
+  "stop_type": "eos|limit|word|none",
+  "stopping_word": "",
+  "completion_probabilities": [...],
+  "generation_settings": {...},
+  "model": "<alias>",
+  "prompt": "<processed prompt>",
+  "tokens_cached": 0,
+  "tokens_evaluated": 0,
+  "truncated": false,
+  "timings": {...}
+}
+```
+
+---
+
+### POST `/tokenize` — Tokenize Text
+
+**Options:**
+
+| Field | Type | Default | Description |
+|-------|------|---------|-------------|
+| `content` | string | required | Text to tokenize |
+| `add_special` | bool | false | Insert special tokens (BOS) |
+| `parse_special` | bool | true | Parse special tokens |
+| `with_pieces` | bool | false | Return token pieces with IDs |
+
+**Response:**
+
+Without pieces: `{"tokens": [123, 456, 789]}`
+
+With pieces: `{"tokens": [{"id": 123, "piece": "Hello"}, ...]}`
+
+---
+
+### POST `/detokenize` — Convert Tokens to Text
+
+**Options:**
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `tokens` | array | Token IDs to detokenize |
+
+---
+
+### POST `/apply-template` — Apply Chat Template
+
+Formats chat messages to a single prompt string without performing inference.
+
+**Options:**
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `messages` | array | Chat turns (same format as `/v1/chat/completions`) |
+
+**Response:** `{"prompt": "<formatted string>"}`
+
+---
+
+### POST `/embedding` — Generate Embedding
+
+> ⚠️ Not OAI-compatible. Use `/v1/embeddings` for OAI clients.
+
+Supports multimodal embeddings.
+
+**Options:**
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `content` | string | Text to embed |
+| `embd_normalize` | int | -1=none, 0=max abs, 1=taxicab, 2=euclidean, >2=p-norm |
+
+---
+
+### POST `/reranking` — Rerank Documents
+
+Aliases: `/rerank`, `/v1/rerank`, `/v1/reranking`
+
+Requires reranker model with `--embedding --pooling rank`.
+
+**Options:**
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `query` | string | Query to rank against |
+| `documents` | array | Array of document strings |
+| `top_n` | int | Top N results |
+
+**Example:**
+
+```shell
+curl http://127.0.0.1:8012/v1/rerank \
+    -H "Content-Type: application/json" \
+    -d '{
+        "model": "some-model",
+        "query": "What is panda?",
+        "top_n": 3,
+        "documents": ["hi", "it is a bear", "The giant panda..."]
+    }'
+```
+
+---
+
+### POST `/infill` — Code Infilling
+
+Takes prefix and suffix, returns predicted completion.
+
+**Options:**
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `input_prefix` | string | Code prefix |
+| `input_suffix` | string | Code suffix |
+| `input_extra` | array | Additional context: `[{"filename": "...", "text": "..."}]` |
+| `prompt` | string | Added after FIM_MID token |
+
+Also accepts all `/completion` options.
+
+**Repo-level pattern** (if model has `FIM_REPO` and `FIM_FILE_SEP`):
+
+```
+<FIM_REP>myproject
+<FIM_SEP>{chunk filename}
+{chunk text}
+...
+<FIM_SEP>filename
+<FIM_PRE>[prefix]<FIM_SUF>[suffix]<FIM_MID>[prompt]
+```
+
+---
+
+### GET `/props` — Server Properties
+
+Returns server global properties including default generation settings, model path, chat template, modalities, and build info.
+
+Enable POST modification with `--props`.
+
+**Response includes:**
+- `default_generation_settings` — default params for `/completion`
+- `total_slots` — number of parallel slots
+- `model_path` — model file path
+- `chat_template` — Jinja2 template
+- `chat_template_caps` — template capabilities
+- `modalities` — supported modalities
+- `is_sleeping` — sleep mode status
+
+---
+
+### GET `/slots` — Slot Monitoring
+
+Returns per-slot processing state, metrics, speed, tokens, sampling parameters.
+
+Disable with `--no-slots`.
+
+Query param `?fail_on_no_slot=1` returns 503 if no slots available.
+
+---
+
+### GET `/metrics` — Prometheus Metrics
+
+Enable with `--metrics`.
+
+**Available metrics:**
+- `llamacpp:prompt_tokens_total` — prompt tokens processed
+- `llamacpp:tokens_predicted_total` — generation tokens processed
+- `llamacpp:prompt_tokens_seconds` — avg prompt throughput (tokens/s)
+- `llamacpp:predicted_tokens_seconds` — avg generation throughput (tokens/s)
+- `llamacpp:kv_cache_usage_ratio` — KV-cache usage (1 = 100%)
+- `llamacpp:kv_cache_tokens` — KV-cache tokens
+- `llamacpp:requests_processing` — requests currently processing
+- `llamacpp:requests_deferred` — requests deferred
+- `llamacpp:n_tokens_max` — high watermark context size
+
+---
+
+### POST `/slots/{id_slot}?action=save` — Save Slot Cache
+
+**Options:** `filename` — file name (saved in `--slot-save-path`)
+
+**Response:** `{"id_slot": 0, "filename": "...", "n_saved": N, "n_written": N, "timings": {...}}`
+
+### POST `/slots/{id_slot}?action=restore` — Restore Slot Cache
+
+**Options:** `filename` — file to restore from `--slot-save-path`
+
+### POST `/slots/{id_slot}?action=erase` — Erase Slot Cache
+
+**Response:** `{"id_slot": 0, "n_erased": N}`
+
+---
+
+### GET `/lora-adapters` — List LoRA Adapters
+
+Returns loaded LoRA adapters with id, path, and scale.
+
+### POST `/lora-adapters` — Set LoRA Adapter Scales
+
+Sets global scale for LoRA adapters. Overridden by per-request `lora` field.
+
+```json
+[{"id": 0, "scale": 0.2}, {"id": 1, "scale": 0.8}]
+```
+
+---
+
+## OpenAI-Compatible API Endpoints
+
+### GET `/v1/models` — Model Info
+
+Returns loaded model information. Always returns single-element list.
+
+`id` defaults to model file path; override with `--alias`.
+
+### POST `/v1/completions` — OAI Completions
+
+Standard OpenAI Completions API. Supports llama.cpp-specific features like `mirostat`.
+
+**Example (Python):**
+
+```python
+import openai
+
+client = openai.OpenAI(
+    base_url="http://localhost:8080/v1",
+    api_key="sk-no-key-required"
+)
+
+completion = client.completions.create(
+    model="davinci-002",
+    prompt="I believe the meaning of life is",
+    max_tokens=8
+)
+```
+
+### POST `/v1/chat/completions` — OAI Chat Completions
+
+Supports ChatML-formatted messages, streaming, function calling, tool use, reasoning, and multimodal input.
+
+**Response includes `timings` object:**
+- `cache_n` — prompt tokens reused from cache
+- `prompt_n` — prompt tokens being processed
+- `predicted_n` — predicted tokens
+
+Total context tokens = `prompt_n + cache_n + predicted_n`
+
+**Additional options:**
+- `response_format` — JSON output with optional schema
+- `chat_template_kwargs` — additional template parameters
+- `reasoning_format` — reasoning parsing mode
+- `generation_prompt` — prefilled generation prompt
+- `parse_tool_calls` — parse tool calls
+- `parallel_tool_calls` — enable parallel tool calls
+
+**Example:**
+
+```python
+client = openai.OpenAI(base_url="http://localhost:8080/v1", api_key="sk-no-key-required")
+
+completion = client.chat.completions.create(
+    model="gpt-3.5-turbo",
+    messages=[
+        {"role": "system", "content": "You are ChatGPT..."},
+        {"role": "user", "content": "Write a limerick about python exceptions"}
+    ]
+)
+```
+
+### POST `/v1/responses` — OAI Responses API
+
+Converts Responses request into Chat Completions request internally.
+
+**Example:**
+
+```python
+response = client.responses.create(
+    model="gpt-4.1",
+    instructions="You are ChatGPT...",
+    input="Write a limerick about python exceptions"
+)
+```
+
+### POST `/v1/embeddings` — OAI Embeddings
+
+Requires model with pooling type other than `none`. Embeddings normalized using Euclidean norm.
+
+Supports string or array of strings as input.
+
+### POST `/v1/messages` — Anthropic-Compatible Messages API
+
+Supports streaming via SSE. Tool use requires `--jinja`.
+
+**Options:**
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `model` | string | Model identifier (required) |
+| `messages` | array | Message objects with role and content (required) |
+| `max_tokens` | int | Max tokens to generate (default: 4096) |
+| `system` | string/array | System prompt |
+| `temperature` | float | Sampling temperature 0-1 (default: 1.0) |
+| `top_p` | float | Nucleus sampling (default: 1.0) |
+| `top_k` | int | Top-k sampling |
+| `stop_sequences` | array | Stop sequences |
+| `stream` | bool | Enable streaming (default: false) |
+| `tools` | array | Tool definitions |
+| `tool_choice` | object | `{"type": "auto"}` / `{"type": "any"}` / `{"type": "tool", "name": "..."}` |
+
+### POST `/v1/messages/count_tokens` — Token Counting
+
+Counts tokens without generating. Same params as `/v1/messages` except `max_tokens`.
+
+**Response:** `{"input_tokens": 10}`
+
+---
+
+## Multiple Models (Router Mode)
+
+Launch without specifying a model to enter router mode:
+
+```sh
+llama-server
+```
+
+### Model Sources
+
+1. **Cached models** (controlled by `LLAMA_CACHE` env var)
+2. **Custom directory** (`--models-dir`)
+3. **Custom preset** (`--models-preset`)
+
+Add Hugging Face models to cache:
+```sh
+llama-server -hf <user>/<model>:<tag>
+```
+
+### Directory Structure for `--models-dir`
+
+```
+models_directory/
+├─ llama-3.2-1b-Q4_K_M.gguf          # single file
+├─ Qwen3-8B-Q4_K_M.gguf              # single file
+├─ gemma-3-4b-it-Q8_0/               # multimodal
+│    ├─ gemma-3-4b-it-Q8_0.gguf
+│    └─ mmproj-F16.gguf
+├─ Kimi-K2-Thinking-UD-IQ1_S/        # multi-shard
+│    ├─ ...-00001-of-00006.gguf
+│    └─ ...-00006-of-00006.gguf
+```
+
+### Model Presets (INI File)
+
+```ini
+version = 1
+
+[*]
+c = 8192
+n-gpu-layers = 8
+
+[ggml-org/MY-MODEL-GGUF:Q8_0]
+chat-template = chatml
+n-gpu-layers = 123
+jinja = true
+c = 4096
+
+[custom_model]
+model = /path/to/my-awesome-model-Q4_K_M.gguf
+```
+
+**Precedence:** CLI args > model-specific preset > global preset `[*]`
+
+**Preset-exclusive options:**
+- `load-on-startup` (bool) — auto-load on server start
+- `stop-timeout` (int, seconds) — wait before forcing termination (default: 10)
+
+### Routing
+
+POST endpoints use `"model"` field in JSON body. GET endpoints use `model` query parameter.
+
+Auto-load can be disabled with `--no-models-autoload` or per-request `?autoload=true|false`.
+
+### Router API Endpoints
+
+#### GET `/models` — List Available Models
+
+Returns all models with status (loaded, loading, sleeping, unloaded, failed).
+
+#### POST `/models/load` — Load a Model
+
+```json
+{"model": "ggml-org/gemma-3-4b-it-GGUF:Q4_K_M"}
+```
+
+#### POST `/models/unload` — Unload a Model
+
+```json
+{"model": "ggml-org/gemma-3-4b-it-GGUF:Q4_K_M"}
+```
+
+---
+
+## Error Format
+
+Errors follow the OpenAI format:
+
+```json
+{
+    "error": {
+        "code": 401,
+        "message": "Invalid API Key",
+        "type": "authentication_error"
+    }
+}
+```
+
+**Custom error types:**
+- `not_supported_error` (501) — disabled endpoint
+- `invalid_request_error` (400) — invalid grammar
+
+---
+
+## Sleeping on Idle
+
+Enable with `--sleep-idle-seconds N`. Unloads model and KV cache after N seconds of inactivity. Any new task triggers reload.
+
+**Exempt endpoints** (don't trigger reload or reset timer): `/health`, `/props`, `/models`
+
+Check status via `GET /props` (`is_sleeping` field).
+
+---
+
+## Web UI
+
+### Custom Default Preferences
+
+```bash
+./llama-server -m model.gguf --webui-config '{"pasteLongTextToFileLen": 0, "renderUserContentAsMarkdown": true}'
+```
+
+### Legacy Completion UI
+
+```sh
+./llama-server -m my_model.gguf -c 8192 --path ./tools/server/public_legacy
+```
+
+### Custom Front End
+
+Serve from `--path ./your-directory` and import `/completion.js` for `llamaComplete()`.
+
+```html
+<html>
+  <body>
+    <pre>
+      <script type="module">
+        import { llama } from '/completion.js'
+        for await (const chunk of llama("Your prompt here")) {
+          document.write(chunk.data.content)
+        }
+      </script>
+    </pre>
+  </body>
+</html>
+```
\ No newline at end of file