> ## Documentation Index > Fetch the complete documentation index at: https://docs2.openclaw.ai/llms.txt > Use this file to discover all available pages before exploring further. # Inference CLI `openclaw infer` is the canonical headless surface for provider-backed inference. It exposes capability families (`model`, `image`, `audio`, `tts`, `video`, `web`, `embedding`), not raw gateway RPC names or agent tool ids. `openclaw capability ...` is an alias for the same command tree. Reasons to prefer it over a one-off provider wrapper: * Reuses providers and models already configured in OpenClaw. * Stable `--json` envelope for scripts and agent-driven automation (see [JSON output](#json-output)). * Runs the normal local path without the gateway for most subcommands. * For end-to-end provider checks, it exercises the shipped CLI, config loading, default-agent resolution, bundled plugin activation, and the shared capability runtime before the provider request goes out. ## Turn infer into a skill Copy and paste this to an agent: ```text theme={"theme":{"light":"min-light","dark":"min-dark"}} Read https://docs.openclaw.ai/cli/infer, then create a skill that routes my common workflows to `openclaw infer`. Focus on model runs, image generation, video generation, audio transcription, TTS, web search, and embeddings. ``` A good infer-based skill maps common user intents to the right subcommand, includes a few canonical examples per workflow, prefers `openclaw infer ...` over lower-level alternatives, and does not re-document the entire infer surface in the skill body. ## Command tree ```text theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer list inspect model run list inspect providers auth login auth logout auth status image generate edit describe describe-many providers audio transcribe providers tts convert voices providers personas status enable disable set-provider set-persona video generate describe providers web search fetch providers embedding create providers ``` `infer list` / `infer inspect --name ` show this tree as data (capability id, transports, description). ## Common tasks | Task | Command | Notes | | ----------------------------- | --------------------------------------------------------------------------------------------- | ----------------------------------------------------- | | Run a text/model prompt | `openclaw infer model run --prompt "..." --json` | Local by default | | Run a model prompt on images | `openclaw infer model run --prompt "Describe this" --file ./image.png --model provider/model` | Repeat `--file` for multiple images | | Generate an image | `openclaw infer image generate --prompt "..." --json` | Use `image edit` when starting from an existing file | | Describe an image file or URL | `openclaw infer image describe --file ./image.png --prompt "..." --json` | `--model` must be an image-capable `` | | Transcribe audio | `openclaw infer audio transcribe --file ./memo.m4a --json` | `--model` must be `` | | Synthesize speech | `openclaw infer tts convert --text "..." --output ./speech.mp3 --json` | `tts status` only runs through the gateway | | Generate a video | `openclaw infer video generate --prompt "..." --json` | Supports provider hints such as `--resolution` | | Describe a video file | `openclaw infer video describe --file ./clip.mp4 --json` | `--model` must be `` | | Search the web | `openclaw infer web search --query "..." --json` | | | Fetch a web page | `openclaw infer web fetch --url https://example.com --json` | | | Create embeddings | `openclaw infer embedding create --text "..." --json` | | ## Behavior * Use `--json` when the output feeds another command or script; text output otherwise. * Use `--provider` or `--model provider/model` to pin a specific backend. * Use `model run --thinking ` for a one-shot thinking/reasoning override: `off`, `minimal`, `low`, `medium`, `high`, `adaptive`, `xhigh`, or `max`. * For `image describe`, `audio transcribe`, and `video describe`, `--model` must use the form ``. * For `image describe`, `--file` accepts local paths and HTTP(S) URLs; remote URLs go through the normal media-fetch SSRF policy. * Stateless execution commands (`model run`, `image *`, `audio *`, `video *`, `web *`, `embedding *`) default to local. Gateway-managed state commands (`tts status`) default to gateway. * The local path never requires the gateway to be running. * Local `model run` is a lean one-shot provider completion: it resolves the configured agent model and auth but does not start a chat-agent turn, load tools, or open bundled MCP servers. * `model run --file` attaches image files (auto-detected MIME type) to the prompt; repeat `--file` for multiple images. Non-image files are rejected — use `infer audio transcribe` or `infer video describe` instead. * `model run --gateway` exercises Gateway routing, saved auth, provider selection, and the embedded runtime, but stays a raw model probe: no prior session transcript, bootstrap/AGENTS context, tools, or bundled MCP servers. * `model run --gateway --model ` requires a trusted-operator gateway credential, because it asks the Gateway to run a one-off provider/model override. ## Model Text inference and model/provider inspection. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer model run --prompt "Reply with exactly: smoke-ok" --json openclaw infer model run --prompt "Summarize this changelog entry" --model openai/gpt-5.4 --json openclaw infer model run --prompt "Describe this image in one sentence" --file ./photo.jpg --model google/gemini-2.5-flash --json openclaw infer model run --prompt "Use more reasoning here" --thinking high --json openclaw infer model providers --json openclaw infer model inspect --model gpt-5.5 --json ``` Use full `` refs with `--local` to smoke-test one provider without starting the Gateway or loading the agent tool surface: ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer model run --local --model anthropic/claude-sonnet-4-6 --prompt "Reply with exactly: pong" --json openclaw infer model run --local --model cerebras/zai-glm-4.7 --prompt "Reply with exactly: pong" --json openclaw infer model run --local --model google/gemini-2.5-flash --prompt "Reply with exactly: pong" --json openclaw infer model run --local --model groq/llama-3.1-8b-instant --prompt "Reply with exactly: pong" --json openclaw infer model run --local --model mistral/mistral-medium-3-5 --prompt "Reply with exactly: pong" --json openclaw infer model run --local --model mistral/mistral-small-latest --prompt "Reply with exactly: pong" --json openclaw infer model run --local --model openai/gpt-5.5 --prompt "Reply with exactly: pong" --json openclaw infer model run --local --model ollama/qwen2.5vl:7b --prompt "Describe this image." --file ./photo.jpg --json ``` Notes: * Local `model run` is the narrowest CLI smoke for provider/model/auth health: for non-ChatGPT-Codex providers it sends only the supplied prompt. * Local `model run --model ` can resolve exact bundled static-catalog rows (the same rows `openclaw models list --all` shows) before that provider is written to config. Provider auth is still required; missing credentials fail as auth errors, not `Unknown model`. * For Mistral Medium 3.5 reasoning probes, leave temperature unset/default. Mistral rejects `reasoning_effort="high"` with `temperature: 0`; use default temperature or a non-zero value such as `0.7`. * OpenAI ChatGPT/Codex OAuth (`openai-chatgpt-responses` API) local probes add a minimal system instruction so the transport can populate its required `instructions` field — no full agent context, tools, memory, or session transcript. * `model run --file` attaches image content directly to the single user message. Common formats (PNG, JPEG, WebP) work when MIME type is detected as `image/*`; unsupported or unrecognized files fail before the provider is called. Use `infer image describe` instead when you want OpenClaw's image-model routing and fallbacks rather than a direct multimodal-model probe. * The selected model must support image input; text-only models may reject the request at the provider layer. * `model run --prompt` must contain non-whitespace text; empty prompts are rejected before any provider or Gateway call. * Local `model run` exits non-zero when the provider returns no text output, so unreachable providers and empty completions do not look like successful probes. * Use `model run --gateway` to test Gateway routing or agent-runtime setup while keeping the model input raw. Use `openclaw agent` or a chat surface for full agent context, tools, memory, and session transcript. * `--thinking adaptive` maps to the completion-runtime level `medium`; `--thinking max` maps to `max` for OpenAI models that support the native max effort, otherwise `xhigh`. * `model auth login`, `model auth logout`, and `model auth status` manage saved provider auth state. ## Image Generation, edit, and description. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer image generate --prompt "friendly lobster illustration" --json openclaw infer image generate --prompt "cinematic product photo of headphones" --json openclaw infer image generate --model openai/gpt-image-1.5 --output-format png --background transparent --prompt "simple red circle sticker on a transparent background" --json openclaw infer image generate --model openai/gpt-image-2 --quality low --openai-moderation low --prompt "low-cost draft poster" --json openclaw infer image generate --prompt "slow image backend" --timeout-ms 180000 --json openclaw infer image edit --file ./logo.png --model openai/gpt-image-1.5 --output-format png --background transparent --prompt "keep the logo, remove the background" --json openclaw infer image edit --file ./poster.png --prompt "make this a vertical story ad" --size 2160x3840 --aspect-ratio 9:16 --resolution 4K --json openclaw infer image describe --file ./photo.jpg --json openclaw infer image describe --file https://example.com/photo.png --json openclaw infer image describe --file ./receipt.jpg --prompt "Extract the merchant, date, and total" --json openclaw infer image describe-many --file ./before.png --file ./after.png --prompt "Compare the screenshots and list visible UI changes" --json openclaw infer image describe --file ./ui-screenshot.png --model openai/gpt-5.4-mini --json openclaw infer image describe --file ./photo.jpg --model ollama/qwen2.5vl:7b --prompt "Describe the image in one sentence" --timeout-ms 300000 --json ``` Notes: * Use `image edit` when starting from existing input files; `--size`, `--aspect-ratio`, or `--resolution` add geometry hints on providers/models that support them. * `--output-format png --background transparent` with `--model openai/gpt-image-1.5` gives transparent-background OpenAI PNG output; `--openai-background` is an OpenAI-specific alias for the same hint. Providers that do not declare background support report it as an ignored override (see `ignoredOverrides` in the [JSON envelope](#json-output)). * `--quality low|medium|high|auto` works for providers that support image-quality hints, including OpenAI. OpenAI also accepts `--openai-moderation low|auto`. * `image providers --json` lists which bundled image providers are discoverable, configured, selected, and which generation/edit capabilities each exposes. * `image generate --model --json` is the narrowest live smoke for image-generation changes: ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer image providers --json openclaw infer image generate \ --model google/gemini-3.1-flash-image-preview \ --prompt "Minimal flat test image: one blue square on a white background, no text." \ --output ./openclaw-infer-image-smoke.png \ --json ``` The response reports `ok`, `provider`, `model`, `attempts`, and written output paths. When `--output` is set, the final extension may follow the provider's returned MIME type. * For `image describe` and `image describe-many`, use `--prompt` for a task-specific instruction (OCR, comparison, UI inspection, concise captioning). * Use `--timeout-ms` for slow local vision models or cold Ollama starts. * For `image describe`, an explicit `--model` (must be an image-capable ``) runs first, then tries configured `agents.defaults.imageModel.fallbacks` if that call fails. Input-preparation errors (missing file, unsupported URL) fail before any fallback attempt, and the model must be image-capable in the model catalog or provider config. * For local Ollama vision models, pull the model first and set `OLLAMA_API_KEY` to any placeholder value, for example `ollama-local`. See [Ollama](/providers/ollama#vision-and-image-description). ## Audio File transcription (not realtime session management). ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer audio transcribe --file ./memo.m4a --json openclaw infer audio transcribe --file ./team-sync.m4a --language en --prompt "Focus on names and action items" --json openclaw infer audio transcribe --file ./memo.m4a --model openai/whisper-1 --json ``` `--model` must be ``. ## TTS Speech synthesis and TTS provider/persona state. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer tts convert --text "hello from openclaw" --output ./hello.mp3 --json openclaw infer tts convert --text "Your build is complete" --output ./build-complete.mp3 --json openclaw infer tts providers --json openclaw infer tts personas --json openclaw infer tts status --json ``` Notes: * `tts status` only supports `--gateway` (it reflects gateway-managed TTS state). * Use `tts providers`, `tts voices`, `tts personas`, `tts set-provider`, and `tts set-persona` to inspect and configure TTS behavior. ## Video Generation and description. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer video generate --prompt "cinematic sunset over the ocean" --json openclaw infer video generate --prompt "slow drone shot over a forest lake" --resolution 768P --duration 6 --json openclaw infer video describe --file ./clip.mp4 --json openclaw infer video describe --file ./clip.mp4 --model openai/gpt-5.4-mini --json ``` Notes: * `video generate` accepts `--size`, `--aspect-ratio`, `--resolution`, `--duration`, `--audio`, `--watermark`, and `--timeout-ms`, forwarded to the video-generation runtime. * `--model` must be `` for `video describe`. ## Web Search and fetch. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer web search --query "OpenClaw docs" --json openclaw infer web search --query "OpenClaw infer web providers" --json openclaw infer web fetch --url https://docs.openclaw.ai/cli/infer --json openclaw infer web providers --json ``` `web providers` lists available, configured, and selected providers for search and fetch. ## Embedding Vector creation and embedding-provider inspection. ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} openclaw infer embedding create --text "friendly lobster" --json openclaw infer embedding create --text "customer support ticket: delayed shipment" --model openai/text-embedding-3-large --json openclaw infer embedding providers --json ``` ## JSON output Infer commands normalize JSON output under a shared envelope: ```json theme={"theme":{"light":"min-light","dark":"min-dark"}} { "ok": true, "capability": "image.generate", "transport": "local", "provider": "openai", "model": "gpt-image-2", "attempts": [], "outputs": [] } ``` Stable top-level fields: * `ok` * `capability` * `transport` * `provider` * `model` * `attempts` * `inputs` (image attachments sent with the request, when applicable) * `outputs` * `ignoredOverrides` (hint keys a provider does not support, when applicable) * `error` For generated media commands, `outputs` contains files written by OpenClaw. Use the `path`, `mimeType`, `size`, and any media-specific dimensions in that array for automation instead of parsing human-readable stdout. ## Common pitfalls ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} # Bad openclaw infer media image generate --prompt "friendly lobster" # Good openclaw infer image generate --prompt "friendly lobster" ``` ```bash theme={"theme":{"light":"min-light","dark":"min-dark"}} # Bad openclaw infer audio transcribe --file ./memo.m4a --model whisper-1 --json # Good openclaw infer audio transcribe --file ./memo.m4a --model openai/whisper-1 --json ``` ## Related * [CLI reference](/cli) * [Models](/concepts/models)