Ollama 400 Unexpected EOF with Cloud Proxy Models on OpenAI-Compatible Endpoint

What this error means

400 unexpected EOF on /v1/chat/completions for cloud proxy models is a Ollama failure pattern reported for developers trying to fix intermittent 400 ‘unexpected eof’ errors when using ollama’s /v1/chat/completions with cloud proxy models. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

Open issue from 2026-05-10. Affects all :cloud models (remote proxy). /v1/chat/completions endpoint returns 400 with ‘unexpected EOF’ or ‘cannot parse request body’. Native /api/chat always works. Error response time 0-11ms. Larger requests (~74KB with tools) fail more frequently. Ollama 0.23.2, Linux WSL2.

Common causes

• Ollama’s cloud proxy models (glm-5.1:cloud, deepseek-v4-pro:cloud, kimi-k2.6:cloud) fail ~5-10% of the time with 400 ‘unexpected EOF’ or ‘cannot parse request body’ on the OpenAI-compatible /v1/chat/completions endpoint. The native /api/chat endpoint works fine, so developers using OpenAI SDK or LangChain hit this unpredictably. Larger request bodies (with tool definitions) fail more often.
• Open issue from 2026-05-10. Affects all :cloud models (remote proxy). /v1/chat/completions endpoint returns 400 with ‘unexpected EOF’ or ‘cannot parse request body’. Native /api/chat always works. Error response time 0-11ms. Larger requests (~74KB with tools) fail more frequently. Ollama 0.23.2, Linux WSL2.

Quick fixes

1. Confirm the exact error signature matches 400 unexpected EOF on /v1/chat/completions for cloud proxy models.
2. Check the Ollama account, local tool state, and provider configuration involved in the failing workflow.
3. Compare the failing environment with a known working setup, then change one configuration value at a time.

Platform/tool-specific checks

• Verify the command, editor, extension, or API client that produced the error.
• Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
• Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

1. Capture the exact error message and the command, editor action, or request that triggered it.
2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
3. Review the source evidence below and compare it with your environment.
4. Apply one change at a time and rerun the smallest failing action.
5. Keep the working fix documented for the team or deployment environment.

How to prevent it

• Keep provider/tool configuration documented.
• Record non-secret diagnostics such as tool version, provider name, model name, and command path.
• Add a lightweight check before CI or production workflows depend on the tool.

Sources checked

• https://github.com/ollama/ollama/issues/16082

Evidence note: Open issue from 2026-05-10. Affects all :cloud models (remote proxy). /v1/chat/completions endpoint returns 400 with ‘unexpected EOF’ or ‘cannot parse request body’. Native /api/chat always works. Error response time 0-11ms. Larger requests (~74KB with tools) fail more frequently. Ollama 0.23.2, Linux WSL2.

Related errors

• Ollama OpenAI API key not found
• Ollama connection refused localhost:11434
• Ollama streaming response cut off

FAQ

What should I check first?

Start with the exact 400 unexpected EOF on /v1/chat/completions for cloud proxy models text and the smallest action that reproduces it.

Can I ignore this error?

No. Treat it as a failed Ollama workflow until the root cause is understood.

Is this guaranteed to have one fix?

No. The imported evidence supports the troubleshooting path above, but tool behavior can vary by account, plan, version, provider, and local configuration.

How do I know the fix worked?

Rerun the same command, editor action, or request. The fix is working when that action completes without 400 unexpected EOF on /v1/chat/completions for cloud proxy models.