Ollama Codex App integration ignores model num_ctx setting, generates excessively large context_window causing severe slowdown

What this error means

Codex App sends requests with context_window=128000-262144 tokens instead of model's configured num_ctx (e.g., 32768) — causing severe generation slowdowns on local models is a Ollama failure pattern reported for developers trying to developers running local ollama models via codex app notice extreme slowdowns; root cause is codex app not reading model parameter num_ctx and defaulting to max context sizes. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub ollama/ollama issue #16188 (created 2026-05-16, updated 2026-05-16) filed against Ollama repo. Directly affects AI coding tool users. Local LLM serving is growing commercial interest area. Category: Ollama (local LLM serving, AI coding tools workflow).

Common causes

• GitHub ollama/ollama issue #16188 (created 2026-05-16, updated 2026-05-16) filed against Ollama repo. Directly affects AI coding tool users. Local LLM serving is growing commercial interest area. Category: Ollama (local LLM serving, AI coding tools workflow).

Quick fixes

1. Confirm the exact error signature matches Codex App sends requests with context_window=128000-262144 tokens instead of model's configured num_ctx (e.g., 32768) — causing severe generation slowdowns on local models.
2. Check the Ollama account, local tool state, and provider configuration involved in the failing workflow.
3. Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.

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/16188

Evidence note: GitHub ollama/ollama issue #16188 (created 2026-05-16, updated 2026-05-16) filed against Ollama repo. Directly affects AI coding tool users. Local LLM serving is growing commercial interest area. Category: Ollama (local LLM serving, AI coding tools workflow).

Related errors

• Ollama

FAQ

What should I check first?

Start with the exact Codex App sends requests with context_window=128000-262144 tokens instead of model's configured num_ctx (e.g., 32768) — causing severe generation slowdowns on local 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 Codex App sends requests with context_window=128000-262144 tokens instead of model's configured num_ctx (e.g., 32768) — causing severe generation slowdowns on local models.