Kimi K1.5vsQwen2.5-Coder
Kimi K1.5 | 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. | — | 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. | 128k | 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. | — | $0.66Cloudflare |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $1.00Cloudflare |
| Overview | ||
| Company | Moonshot AI | Qwen |
| Release date | Jan 20 2025 | Nov 12 2024 |
| Access | Proprietary | Open Weight |
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Frequently asked questions
Kimi K1.5 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 69 days before Kimi K1.5, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (Kimi K1.5) vs 128k (Qwen2.5-Coder). Kimi K1.5 is proprietary, while Qwen2.5-Coder is open weight.
Direct benchmark comparisons are unavailable — Kimi K1.5 and Qwen2.5-Coder don't publish scores on any of the same benchmarks.