---
title: Venice: Uncensored (free) — Uncensored LLM | ModelsLab
description: Access Venice: Uncensored (free) LLM via API for private, unrestricted text generation with 32k context. Try the free uncensored model now.
url: https://modelslab.com/venice-uncensored-free
canonical: https://modelslab.com/venice-uncensored-free
type: website
component: Seo/ModelPage
generated_at: 2026-07-01T04:02:31.617205Z
---

Available now on ModelsLab · Language Model

Venice: Uncensored (free)
Uncensored LLM Free
---

[Try Venice: Uncensored (free)](/models/open_router/cognitivecomputations-dolphin-mistral-24b-venice-edition-free) [API Documentation](https://docs.modelslab.com)

Run Uncensored Models Now
---

32k Context

### Long Context Window

Handles 32,768 tokens for extended conversations and complex prompts.

User Control

### Steerable Alignment

Preserves control over system prompts and behavior in Venice: Uncensored (free).

Text Only

### Text-to-Text Modality

Supports parameters like temperature and frequency\_penalty for precise outputs.

Examples

See what Venice: Uncensored (free) can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/cognitivecomputations-dolphin-mistral-24b-venice-edition-free).

Code Review

“Review this Python function for bugs and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)”

Tech Summary

“Summarize the key advancements in transformer models since 2017, focusing on efficiency improvements.”

Logic Puzzle

“Solve this riddle: I speak without a mouth and hear without ears. I have no body, but I come alive with the wind. What am I?”

Essay Outline

“Create a detailed outline for a 2000-word essay on quantum computing applications in cryptography.”

For Developers

A few lines of code.
Uncensored LLM. One call.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Venice: Uncensored (free)
---

[Read the docs ](https://docs.modelslab.com)

### What is Venice: Uncensored (free)?

Venice: Uncensored (free) is a fine-tuned Dolphin Mistral 24B model for uncensored text generation. It offers 32,768 token context and user-controlled alignment. Access it free via API.

### How to use Venice Uncensored free API?

Use OpenAI-compatible endpoints with model ID cognitivecomputations/dolphin-mistral-24b-venice-edition:free. Set parameters like temperature and top_p. Input and output are text only.

### Is Venice: Uncensored (free) model private?

Yes, built on Venice.ai's privacy-first architecture with no data collection. Prompts stay local where supported. Ideal for unrestricted use.

### What is the context length of venice uncensored free?

It supports 32,768 tokens for input context. Max output varies by provider, up to 8k tokens in some setups.

### Venice: Uncensored (free) alternative to what?

Serves as a free uncensored alternative to censored LLMs like ChatGPT. Provides raw outputs without safety guardrails.

### Venice: Uncensored (free) LLM pricing?

Free tier at $0 per million tokens on select providers. Pro options available for higher limits.

Ready to create?
---

Start generating with Venice: Uncensored (free) on ModelsLab.

[Try Venice: Uncensored (free)](/models/open_router/cognitivecomputations-dolphin-mistral-24b-venice-edition-free) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

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*Generated by ModelsLab - 2026-07-01*