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GPT-5.1-Codex-Mini vs Kimi K2.6 (free)
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
GPT-5.1-Codex-Mini
Context window
400K
400,000 tokens · ~300K words
Model
Kimi K2.6 (free)
Context window
262K
262,144 tokens · ~197K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
GPT-5.1-Codex-Mini has about 1.5× the context window of the other in this pair.
GPT-5.1-Codex-Mini has 52% more context capacity (400K vs 262K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use GPT-5.1-Codex-Mini. Its 400K context fits entire documents without chunking (vs 262K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | GPT-5.1-Codex-Mini | Kimi K2.6 (free) |
|---|---|---|
| Context window | 400,000 tokens (400K) | 262,144 tokens (262K) |
| Max output tokens | 100,000 tokens (100K) | N/A |
| Speed tier | Fast | Balanced |
| Vision | Yes | Yes |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API | No | No |
| Release date | Nov 2025 | Apr 2026 |
Frequently asked questions
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Use a smaller model.
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Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model