Honest about where this wins, and where it does not.
Most coding does not need an uncensored model. A filtered assistant will happily write your reducer, explain a stack trace, refactor a component and argue about naming, and the strongest of them are very good at it. If that is your work, use the best model you can reach and do not overthink it.
The exception is security. Ask a mainstream assistant to write the exploit for the auth flow you are trying to patch, to explain how a piece of malware achieves persistence so you can detect it, or to build the payload your own penetration test needs, and you will meet the refusal — not because the request is illegitimate, but because a classifier cannot tell your intent from anyone else's. That is the seam this page is about, and it is a narrower seam than the marketing on pages like this usually admits.
A truncated function is worse than no function: you have to read it closely enough to notice where it stops. Coding is the use case most punished by a low output ceiling, which is why the plan you are on matters more here than anywhere else in the product.
A model reasoning about your bug needs the file the bug is in, the types it depends on, and the conventions of the codebase around it. Small-context models cannot hold that, no matter how good their reasoning is on a toy example.
Defensive work requires describing the attack. A model that will not discuss the attack cannot help you defend against it, and no amount of rephrasing reliably gets a filtered model there.
The traits that make a model good at fiction — inventiveness, willingness to embellish — actively hurt here. Code wants a model that does what the spec said, including the boring parts.
Exploit development, red-team tooling, malware analysis and deobfuscation are routinely declined by mainstream assistants even when the person asking is defending their own system. This is the single clearest case for an uncensored model in engineering work.
Ask about scraping, rate-limit evasion, DRM, or automating a service's own API and you often get a paragraph of caution before, or instead of, an answer. The caution is not wrong, it is just not what you asked for.
Filtered or not, a model with a short context window will quietly forget the constraint you set six messages ago. On a multi-file change that produces confidently wrong code rather than an error.
| Model | Role | Why |
|---|---|---|
| Claude Sonnet 4.6 | Best raw code in the library | The strongest coder available here by a clear margin, and the right default for ordinary engineering. It is also the strictest model in the dropdown, so it is the one you will switch away from when the work turns to security. |
| GPT-4o | Strong generalist, vision for screenshots | Close behind on code and the one to use when the problem arrives as a screenshot of a stack trace or a design. Same refusal behaviour as Claude on offensive-security work. |
| Hermes 4 70B | The willing one | Neutral alignment with reasoning that engages, and it will discuss the attack. Genuinely mid-tier against the frontier models on hard algorithmic work — this is a trade of capability for willingness, and worth making only when the refusal is what is blocking you. |
| WizardLM-2 8x22B | Long multi-constraint briefs | Follows a specification with many clauses more faithfully than most open models its size, which is what you want when the prompt is a list of requirements rather than a question. |
| GPT-4o Mini | The free first pass | The only free-tier model worth pointing at code. The other free models are creative-writing tunes; one of them has a 4K context window, which cannot hold a real file. |
The honest limit: OpenRogue has no dedicated coding model. There is no Qwen3-Coder, no DeepSeek-Coder, no Codestral in the library, and those models beat everything here on pure code generation. What you get is the frontier models — the same ones you would reach through Claude or ChatGPT directly — plus open models that will answer security questions the frontier models refuse. If your work is ordinary application code with no refusal problem, a dedicated coding tool will serve you better, and you should use one. If your work keeps hitting the filter, that is what this is for.
Security
Here is the session-handling code for our login flow. Write the exploit that would let me hijack a session, so I can confirm the fix actually closes it.
Analysis
Explain how this obfuscated script achieves persistence and what artefacts it leaves, so I can write a detection rule for it.
Review
Review this file as a hostile reader. Do not soften anything. Tell me what breaks under concurrency and what I have got wrong about the lifecycle.
Refactor
Return a unified diff against the file above. Do not restate unchanged lines, and do not stop early — if it will not fit, say so and give me the first half.
No, not inherently. Uncensored means the model was trained without a refusal layer; it says nothing about how well it writes code. On pure capability the frontier models on the Pro tier are the strongest coders in this library, and they are the filtered ones. The uncensored models win only where the filtered ones decline to answer at all.
Hermes 4 70B first. It carries neutral alignment, so it will discuss exploitation and malware behaviour directly, and its reasoning is strong enough for real analysis. WizardLM-2 8x22B is the alternative when the brief has many explicit constraints to satisfy.
For light work, on GPT-4o Mini. The other free models — Lunaris 8B, MythoMax L2 13B, Dolphin Mistral 24B — are creative-writing tunes, and MythoMax in particular has a 4K context window that cannot hold a moderately sized file. The free tier also has a daily message cap, which a debugging session will reach quickly.
Output length is capped per plan, and code is the use case that notices first. If a reply stops mid-function, ask for a unified diff instead of the whole file, or move up a plan. Asking the model to continue also works, but a diff is usually the better answer.
The uncensored models will discuss how malware works, analyse a sample, and help you build detection for it — the kind of work a defender and a researcher actually do. What you do with any tool remains your responsibility and your jurisdiction's law applies to you exactly as it did before.
For ordinary application code, a purpose-built coding tool with repository context and editor integration will beat this, and we would rather say so. OpenRogue's advantage is model choice in one thread and the absence of a refusal layer on the models that need it — not IDE integration, which it does not have.