Guide · Updated June 2026

The best LLM for OpenHands

OpenHands takes a task and runs with it — writing code, executing it in a sandbox, reading the output, and iterating, often for many minutes unattended. That's the single workload most likely to expose a model backend's weak spots: provider rate limits and empty tool turns. CodeBurst gives OpenHands an OpenAI-compatible endpoint that fails over across providers and repairs tool turns, so a long run reaches the finish line.

Long unattended runs are where backends fail

A quick prompt rarely trips anything. A 20-minute OpenHands task firing call after call is a different story:

Because the run is unattended, you often don't notice until you come back to a half-finished task.

What CodeBurst adds

FailureCodeBurst
Provider rate-limits mid-taskReroutes to a healthy provider in the same request — the run continues.
Empty tool-synthesis turncodeburst-agent retries with a corrected format.
Context grows past the windowRoute a compaction step through codeburst-compress (size-aware).

Configure OpenHands

OpenHands uses LiteLLM, so reference the OpenAI-compatible endpoint with the openai/ prefix. In config.toml:

[llm]
model = "openai/codeburst-agent"
base_url = "https://codeburst.ai/api/v1"
api_key = "YOUR_CODEBURST_KEY"

Or set them as environment variables instead:

export LLM_MODEL="openai/codeburst-agent"
export LLM_BASE_URL="https://codeburst.ai/api/v1"
export LLM_API_KEY="YOUR_CODEBURST_KEY"

Nothing else about your OpenHands setup changes — it just stops depending on a single provider being up for the whole run.

Get started

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FAQ

How do I set CodeBurst as the OpenHands LLM?
In [llm]: model="openai/codeburst-agent", base_url="https://codeburst.ai/api/v1", your key — or the LLM_* env vars.

Why a router for OpenHands?
Long unattended runs hit rate limits and empty tool turns; CodeBurst fails over and repairs them so the task finishes.

Does the openai/ prefix matter?
Yes — OpenHands uses LiteLLM slugs, so it's openai/codeburst-agent.