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Kimi K2 Thinking 251104 vs Openai Gpt 4o Mini
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
Kimi K2 Thinking 251104
Context window
229K
229,376 tokens · ~172K 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.
Kimi K2 Thinking 251104 has about 1.8× the context window of the other in this pair.
Kimi K2 Thinking 251104 has 79% more context capacity (229K vs 128K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Kimi K2 Thinking 251104. Its 229K context fits entire documents without chunking (vs 128K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Kimi K2 Thinking 251104 | Openai Gpt 4o Mini |
|---|---|---|
| Context window | 229,376 tokens (229K) | 128,000 tokens (128K) |
| Max output tokens | 32,768 tokens (32K) | N/A |
| Speed tier | Deep | Fast |
| Vision | No | No |
| Function calling | Yes | No |
| Extended thinking | Yes | No |
| Prompt caching | No | No |
| Batch API | No | Yes |
| Release date | N/A | N/A |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | Kimi K2 Thinking 251104 in | Kimi K2 Thinking 251104 out | Openai Gpt 4o Mini in | Openai Gpt 4o Mini out |
|---|---|---|---|---|
| Gradient | — | — | — | — |
| Volcengine | — | — | — | — |
Frequently asked questions
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Example: a multi-turn chat session
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