Ollama / Ollama

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

Fix intermittent 400 'unexpected EOF' errors when using Ollama's /v1/chat/completions with cloud proxy models Includes evidence for Ollama troubleshooting demand.

Source-backed Last updated May 11, 2026 1 source Needs local verification

Category: Ollama
Error signature: 400 unexpected EOF on /v1/chat/completions for cloud proxy models
Quick fix: Compare the failing environment with a known working setup, then change one configuration value at a time.
Updated: May 11, 2026
Verification status: Source-backed
Evidence: 1 public source URL

Before you change production

This page includes public source URLs in the imported troubleshooting record. Compare those references with your version and environment before applying changes.

Reproduce the smallest failing action and save non-secret logs before changing configuration.
Check versions for Ollama, related SDKs, package managers, CI runners, and hosting providers.
Change one setting or dependency at a time, then rerun the same failing command or request.
Avoid destructive commands, credential rotation, billing changes, or security relaxations without a rollback plan.

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

Confirm the exact error signature matches 400 unexpected EOF on /v1/chat/completions for cloud proxy models.
Check the Ollama account, local tool state, and provider configuration involved in the failing workflow.
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

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

Diagnostic flow for this page

Match 400 unexpected EOF on /v1/chat/completions for cloud proxy models exactly before applying the quick fix.
Compare the failing environment with Ollama versions, account scope, provider settings, and deployment context.
Check the listed common causes in order, starting with the cause that best matches your logs.
Use the evidence status below to decide whether to confirm against public sources or official documentation.
Apply one reversible change, rerun the smallest failing action, and keep rollback notes.

FAQ

What does 400 unexpected EOF on /v1/chat/completions for cloud proxy models mean in Ollama?

400 unexpected EOF on /v1/chat/completions for cloud proxy models indicates the workflow described by "Ollama 400 Unexpected EOF with Cloud Proxy Models on OpenAI-Compatible Endpoint" failed in a Ollama context. Start by confirming the exact signature and the component that emitted it.

What should I check first for 400 unexpected EOF on /v1/chat/completions for cloud proxy models?

Check whether this cause matches your environment: 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.

Is the 400 unexpected EOF on /v1/chat/completions for cloud proxy models guidance source-backed?

The "Ollama 400 Unexpected EOF with Cloud Proxy Models on OpenAI-Compatible Endpoint" page is labeled source-backed. It has 1 public source URL from github.com, so use that evidence status when deciding how much additional verification you need.

When should I avoid the quick fix for 400 unexpected EOF on /v1/chat/completions for cloud proxy models?

For "Ollama 400 Unexpected EOF with Cloud Proxy Models on OpenAI-Compatible Endpoint", avoid applying "Compare the failing environment with a known working setup, then change one configuration value at a time." when the error text differs, the affected version or provider is different, or the change would touch credentials, billing, DNS, production deploy settings, or irreversible data.

What should I collect before debugging 400 unexpected EOF on /v1/chat/completions for cloud proxy models?

For "Ollama 400 Unexpected EOF with Cloud Proxy Models on OpenAI-Compatible Endpoint", collect the failing Ollama command or request, non-secret configuration, versions, timestamps, request IDs when available, and the smallest reproduction that still triggers the signature.