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:

# 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

openclaw onboard --auth-choice venice-api-key

export VENICE_API_KEY="vapi_xxxxxxxxxxxx"

openclaw onboard --non-interactive \
  --auth-choice venice-api-key \
  --venice-api-key "vapi_xxxxxxxxxxxx"

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:

openclaw models set venice/kimi-k2-5
openclaw models set venice/claude-opus-4-6

List all available models:

openclaw models list --all --provider venice

You can also run openclaw configure, select Model/auth, and choose Venice AI.

# 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 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

# Pricing

Venice uses a credit-based system. Check 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

# Usage examples

# 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

echo $VENICE_API_KEY
openclaw models list | grep venice

# Advanced configuration

{
  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