--- summary: "Use Venice AI privacy-focused models in OpenClaw" read_when: - You want privacy-focused inference in OpenClaw - You want Venice AI setup guidance title: "Venice AI" --- Venice AI provides **privacy-focused AI inference** with support for uncensored models and access to major proprietary models through their anonymized proxy. All inference is private by default — no training on your data, no logging. ## Why Venice in OpenClaw - **Private inference** for open-source models (no logging). - **Uncensored models** when you need them. - **Anonymized access** to proprietary models (Opus/GPT/Gemini) when quality matters. - OpenAI-compatible `/v1` endpoints. ## Privacy modes Venice offers two privacy levels — understanding this is key to choosing your model: | Mode | Description | Models | | -------------- | --------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------- | | **Private** | Fully private. Prompts/responses are **never stored or logged**. Ephemeral. | Llama, Qwen, DeepSeek, Kimi, MiniMax, Venice Uncensored, etc. | | **Anonymized** | Proxied through Venice with metadata stripped. The underlying provider (OpenAI, Anthropic, Google, xAI) sees anonymized requests. | Claude, GPT, Gemini, Grok | Anonymized models are **not** fully private. Venice strips metadata before forwarding, but the underlying provider (OpenAI, Anthropic, Google, xAI) still processes the request. Choose **Private** models when full privacy is required. ## Features - **Privacy-focused**: Choose between "private" (fully private) and "anonymized" (proxied) modes - **Uncensored models**: Access to models without content restrictions - **Major model access**: Use Claude, GPT, Gemini, and Grok via Venice's anonymized proxy - **OpenAI-compatible API**: Standard `/v1` endpoints for easy integration - **Streaming**: Supported on all models - **Function calling**: Supported on select models (check model capabilities) - **Vision**: Supported on models with vision capability - **No hard rate limits**: Fair-use throttling may apply for extreme usage ## Getting started 1. Sign up at [venice.ai](https://venice.ai) 2. Go to **Settings > API Keys > Create new key** 3. Copy your API key (format: `vapi_xxxxxxxxxxxx`) Choose your preferred setup method: ```bash openclaw onboard --auth-choice venice-api-key ``` This will: 1. Prompt for your API key (or use existing `VENICE_API_KEY`) 2. Show all available Venice models 3. Let you pick your default model 4. Configure the provider automatically ```bash export VENICE_API_KEY="vapi_xxxxxxxxxxxx" ``` ```bash openclaw onboard --non-interactive \ --auth-choice venice-api-key \ --venice-api-key "vapi_xxxxxxxxxxxx" ``` ```bash openclaw agent --model venice/kimi-k2-5 --message "Hello, are you working?" ``` ## Model selection After setup, OpenClaw shows all available Venice models. Pick based on your needs: - **Default model**: `venice/kimi-k2-5` for strong private reasoning plus vision. - **High-capability option**: `venice/claude-opus-4-6` for the strongest anonymized Venice path. - **Privacy**: Choose "private" models for fully private inference. - **Capability**: Choose "anonymized" models to access Claude, GPT, Gemini via Venice's proxy. Change your default model anytime: ```bash openclaw models set venice/kimi-k2-5 openclaw models set venice/claude-opus-4-6 ``` List all available models: ```bash openclaw models list --all --provider venice ``` You can also run `openclaw configure`, select **Model/auth**, and choose **Venice AI**. Use the table below to pick the right model for your use case. | Use Case | Recommended Model | Why | | -------------------------- | -------------------------------- | -------------------------------------------- | | **General chat (default)** | `kimi-k2-5` | Strong private reasoning plus vision | | **Best overall quality** | `claude-opus-4-6` | Strongest anonymized Venice option | | **Privacy + coding** | `qwen3-coder-480b-a35b-instruct` | Private coding model with large context | | **Private vision** | `kimi-k2-5` | Vision support without leaving private mode | | **Fast + cheap** | `qwen3-4b` | Lightweight reasoning model | | **Complex private tasks** | `deepseek-v3.2` | Strong reasoning, but no Venice tool support | | **Uncensored** | `venice-uncensored` | No content restrictions | ## DeepSeek V4 replay behavior If Venice exposes DeepSeek V4 models such as `venice/deepseek-v4-pro` or `venice/deepseek-v4-flash`, OpenClaw fills the required DeepSeek V4 `reasoning_content` replay placeholder on assistant messages when the proxy omits it. Venice rejects DeepSeek's native top-level `thinking` control, so OpenClaw keeps that provider-specific replay fix separate from the native DeepSeek provider's thinking controls. ## Built-in catalog (41 total) | Model ID | Name | Context | Features | | -------------------------------------- | ----------------------------------- | ------- | -------------------------- | | `kimi-k2-5` | Kimi K2.5 | 256k | Default, reasoning, vision | | `kimi-k2-thinking` | Kimi K2 Thinking | 256k | Reasoning | | `llama-3.3-70b` | Llama 3.3 70B | 128k | General | | `llama-3.2-3b` | Llama 3.2 3B | 128k | General | | `hermes-3-llama-3.1-405b` | Hermes 3 Llama 3.1 405B | 128k | General, tools disabled | | `qwen3-235b-a22b-thinking-2507` | Qwen3 235B Thinking | 128k | Reasoning | | `qwen3-235b-a22b-instruct-2507` | Qwen3 235B Instruct | 128k | General | | `qwen3-coder-480b-a35b-instruct` | Qwen3 Coder 480B | 256k | Coding | | `qwen3-coder-480b-a35b-instruct-turbo` | Qwen3 Coder 480B Turbo | 256k | Coding | | `qwen3-5-35b-a3b` | Qwen3.5 35B A3B | 256k | Reasoning, vision | | `qwen3-next-80b` | Qwen3 Next 80B | 256k | General | | `qwen3-vl-235b-a22b` | Qwen3 VL 235B (Vision) | 256k | Vision | | `qwen3-4b` | Venice Small (Qwen3 4B) | 32k | Fast, reasoning | | `deepseek-v3.2` | DeepSeek V3.2 | 160k | Reasoning, tools disabled | | `venice-uncensored` | Venice Uncensored (Dolphin-Mistral) | 32k | Uncensored, tools disabled | | `mistral-31-24b` | Venice Medium (Mistral) | 128k | Vision | | `google-gemma-3-27b-it` | Google Gemma 3 27B Instruct | 198k | Vision | | `openai-gpt-oss-120b` | OpenAI GPT OSS 120B | 128k | General | | `nvidia-nemotron-3-nano-30b-a3b` | NVIDIA Nemotron 3 Nano 30B | 128k | General | | `olafangensan-glm-4.7-flash-heretic` | GLM 4.7 Flash Heretic | 128k | Reasoning | | `zai-org-glm-4.6` | GLM 4.6 | 198k | General | | `zai-org-glm-4.7` | GLM 4.7 | 198k | Reasoning | | `zai-org-glm-4.7-flash` | GLM 4.7 Flash | 128k | Reasoning | | `zai-org-glm-5` | GLM 5 | 198k | Reasoning | | `minimax-m21` | MiniMax M2.1 | 198k | Reasoning | | `minimax-m25` | MiniMax M2.5 | 198k | Reasoning | | Model ID | Name | Context | Features | | ------------------------------- | ------------------------------ | ------- | ------------------------- | | `claude-opus-4-6` | Claude Opus 4.6 (via Venice) | 1M | Reasoning, vision | | `claude-opus-4-5` | Claude Opus 4.5 (via Venice) | 198k | Reasoning, vision | | `claude-sonnet-4-6` | Claude Sonnet 4.6 (via Venice) | 1M | Reasoning, vision | | `claude-sonnet-4-5` | Claude Sonnet 4.5 (via Venice) | 198k | Reasoning, vision | | `openai-gpt-54` | GPT-5.4 (via Venice) | 1M | Reasoning, vision | | `openai-gpt-53-codex` | GPT-5.3 Codex (via Venice) | 400k | Reasoning, vision, coding | | `openai-gpt-52` | GPT-5.2 (via Venice) | 256k | Reasoning | | `openai-gpt-52-codex` | GPT-5.2 Codex (via Venice) | 256k | Reasoning, vision, coding | | `openai-gpt-4o-2024-11-20` | GPT-4o (via Venice) | 128k | Vision | | `openai-gpt-4o-mini-2024-07-18` | GPT-4o Mini (via Venice) | 128k | Vision | | `gemini-3-1-pro-preview` | Gemini 3.1 Pro (via Venice) | 1M | Reasoning, vision | | `gemini-3-pro-preview` | Gemini 3 Pro (via Venice) | 198k | Reasoning, vision | | `gemini-3-flash-preview` | Gemini 3 Flash (via Venice) | 256k | Reasoning, vision | | `grok-41-fast` | Grok 4.1 Fast (via Venice) | 1M | Reasoning, vision | | `grok-code-fast-1` | Grok Code Fast 1 (via Venice) | 256k | Reasoning, coding | ## Model discovery OpenClaw ships a manifest-backed Venice seed catalog for read-only model listing. Runtime refresh can still discover models from the Venice API, and falls back to the manifest catalog if the API is unreachable. The `/models` endpoint is public (no auth needed for listing), but inference requires a valid API key. ## Streaming and tool support | Feature | Support | | -------------------- | ---------------------------------------------------- | | **Streaming** | All models | | **Function calling** | Most models (check `supportsFunctionCalling` in API) | | **Vision/Images** | Models marked with "Vision" feature | | **JSON mode** | Supported via `response_format` | ## Pricing Venice uses a credit-based system. Check [venice.ai/pricing](https://venice.ai/pricing) for current rates: - **Private models**: Generally lower cost - **Anonymized models**: Similar to direct API pricing + small Venice fee ### Venice (anonymized) vs direct API | Aspect | Venice (Anonymized) | Direct API | | ------------ | ----------------------------- | ------------------- | | **Privacy** | Metadata stripped, anonymized | Your account linked | | **Latency** | +10-50ms (proxy) | Direct | | **Features** | Most features supported | Full features | | **Billing** | Venice credits | Provider billing | ## Usage examples ```bash # Use the default private model openclaw agent --model venice/kimi-k2-5 --message "Quick health check" # Use Claude Opus via Venice (anonymized) openclaw agent --model venice/claude-opus-4-6 --message "Summarize this task" # Use uncensored model openclaw agent --model venice/venice-uncensored --message "Draft options" # Use vision model with image openclaw agent --model venice/qwen3-vl-235b-a22b --message "Review attached image" # Use coding model openclaw agent --model venice/qwen3-coder-480b-a35b-instruct --message "Refactor this function" ``` ## Troubleshooting ```bash echo $VENICE_API_KEY openclaw models list | grep venice ``` Ensure the key starts with `vapi_`. The Venice model catalog updates dynamically. Run `openclaw models list` to see currently available models. Some models may be temporarily offline. Venice API is at `https://api.venice.ai/api/v1`. Ensure your network allows HTTPS connections. More help: [Troubleshooting](/help/troubleshooting) and [FAQ](/help/faq). ## Advanced configuration ```json5 { env: { VENICE_API_KEY: "vapi_..." }, agents: { defaults: { model: { primary: "venice/kimi-k2-5" } } }, models: { mode: "merge", providers: { venice: { baseUrl: "https://api.venice.ai/api/v1", apiKey: "${VENICE_API_KEY}", api: "openai-completions", models: [ { id: "kimi-k2-5", name: "Kimi K2.5", reasoning: true, input: ["text", "image"], cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 }, contextWindow: 256000, maxTokens: 65536, }, ], }, }, }, } ``` ## Related Choosing providers, model refs, and failover behavior. Venice AI homepage and account signup. Venice API reference and developer docs. Current Venice credit rates and plans.