Kimi K2 ThinkingvsQwen2.5-Coder
Kimi K2 Thinking | Qwen2.5-Coder | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | 1T | 32B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 256k | 128k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.60Google | $0.66Cloudflare |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $2.50Google | $1.00Cloudflare |
| BenchmarksPublished by one model only | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 71.3% | — |
| Overview | ||
| Company | Moonshot AI | Qwen |
| Release date | Nov 6 2025 | Nov 12 2024 |
| Access | Open Weight | Open Weight |
Other comparisons
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Frequently asked questions
Kimi K2 Thinking and Qwen2.5-Coder don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen2.5-Coder shipped 359 days before Kimi K2 Thinking, so benchmark comparisons should account for the intervening progress.
Kimi K2 Thinking has 1T parameters, while Qwen2.5-Coder has 32B. Context windows are 256k (Kimi K2 Thinking) vs 128k (Qwen2.5-Coder).
Direct benchmark comparisons are unavailable — Kimi K2 Thinking and Qwen2.5-Coder don't publish scores on any of the same benchmarks.