The best uncensored LLMs in 2026
There's no single best uncensored model — there's the best one for your task, hardware and tolerance for ops work. Here are the options worth knowing, what each is good at, and how to choose.
Quick comparison
| Hosted UM models | Abliterated open models | Dolphin / Hermes fine-tunes | |
|---|---|---|---|
| Low refusal rate | ✓ | ✓ | ✓ |
| Quality vs. base model | Retained (SFT + DPO) | Small regressions possible | Depends on base & data |
| Context window | 32K–128K | Base model's | Base model's |
| Web search, memory, tools | ✓ | ✕ | ~ |
| Runs offline / fully private | ✕ | ✓ | ✓ |
| Hardware needed | None | Your GPU / Mac | Your GPU / Mac |
| Cost | 1M tok free, then per token | Free weights + hardware | Free weights + hardware |
1. UM models (UncensoredModel.ai) — best hosted option
Disclosure: these are ours. The UM family ranges from UM-7B (fast, cheap, high-volume) to UM-70B (flagship depth for creative and long-form work), plus reasoning variants that show their chain-of-thought. They're trained with SFT and DPO specifically to answer sensitive-but-legitimate questions while keeping hard limits on clearly illegal content.
- Best for: developers who want an OpenAI-compatible uncensored API, and anyone who wants to chat without installing anything.
- Strengths: up to 128K context, built-in web search, memory and tool calling, no hardware.
- Trade-offs: not offline; adult content requires 18+ verification.
See the full lineup on the models page.
2. Abliterated open models — best for quick local use
Within days of a popular open model's release (Llama, Qwen, Mistral, Gemma and others), the community usually publishes an abliterated version: the internal refusal direction is identified and removed from the weights. You get the base model's knowledge and style, minus most refusals.
- Best for: trying the newest open models uncensored, privacy-sensitive local use.
- Strengths: available for almost every major release, in many sizes and quantisations.
- Trade-offs: quality varies by who made it; some show small regressions or odd behaviour. Look for versions that were “healed” with a short fine-tune afterwards.
3. Dolphin fine-tunes — the classic uncensored family
Dolphin is one of the best-known uncensored model lines. Its approach is to fine-tune open base models on instruction data with refusals and moralising filtered out, so the model is compliant by design. Dolphin models are typically meant to be paired with your own system prompt and safety layer.
- Best for: general-purpose uncensored assistants and coding help, run locally.
- Trade-offs: quality tracks the underlying base model; check which base and size a given release uses.
4. Nous Hermes — steerable, system-prompt-driven
The Hermes series from Nous Research focuses on strong instruction-following and steerability. Rather than baking in a fixed persona or heavy refusals, Hermes models largely do what the system prompt tells them, which makes them popular for agents, tool use and roleplay.
- Best for: builders who want control via the system prompt, function calling, structured output.
- Trade-offs: “low refusal” rather than strictly uncensored by default — behaviour depends on how you prompt it.
5. Community roleplay & creative fine-tunes
There's a large ecosystem of community fine-tunes and merges aimed at fiction, character chat and roleplay, often built on larger open models. The best ones produce vivid, consistent long-form writing; the worst are unstable merges. Community leaderboards and model cards with sample outputs are the best way to judge them.
How we picked — and how you should choose
Benchmarks for “uncensoredness” are noisy and easy to game, so we look at five practical criteria instead of a single score:
- Refusal rate on legitimate requests. Test the model with 20–50 questions from your domain — medical, security, fiction — and count refusals, hedges and watered-down answers.
- Quality retention. Uncensoring shouldn't cost reasoning. Compare a few hard, non-sensitive tasks (math, code, summarisation) against the base model.
- Context length. Long documents, RAG and long roleplay sessions need 32K+ context; 128K is comfortable.
- Licence. Open-weight licences differ — some restrict commercial use or require attribution. Read it before you ship.
- Hardware and ops. A quantised 7–9B model runs on a laptop; a 70B model needs serious GPU memory. If you don't want to manage that, a hosted model is cheaper in practice. See hosted vs self-hosted.
Our recommendation
- Building an app or agent? Use a hosted uncensored API so you get uptime, tools and scaling. Start with UM-14B or UM-32B.
- Creative writing or roleplay? Go big — 70B-class models are clearly better at long-form fiction.
- Maximum privacy, offline? Pick a recent abliterated or Dolphin/Hermes-style model that fits your GPU.
- Just curious? Open the uncensored AI chat and ask the questions other assistants refused.
New to the topic? Start with what an uncensored LLM actually is.
Frequently asked questions
What is the best uncensored LLM?
What's the best uncensored model for roleplay and creative writing?
What's the best small uncensored LLM to run on a laptop?
Do abliterated models lose quality?
Are these models free?
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