Kimi K1.5vsQwen3
Kimi K1.5 | Qwen3 | |
|---|---|---|
| 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. | — | 235B |
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 · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $0.70 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $2.80 |
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. | — | $0.0482StreamLake |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $0.1931StreamLake |
| Overview | ||
| Company | Moonshot AI | Qwen |
| Release date | Jan 20 2025 | Apr 29 2025 |
| Access | Proprietary | Open Weight |
Other comparisons
Frequently asked questions
Kimi K1.5 and Qwen3 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Qwen3 has a verified first-party API price: $0.70 per million input tokens and $2.80 per million output tokens. No pay-as-you-go API rate is tracked for Kimi K1.5. Kimi K1.5 shipped 99 days before Qwen3, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (Kimi K1.5) vs 128k (Qwen3). Kimi K1.5 is proprietary, while Qwen3 is open weight.
Direct benchmark comparisons are unavailable — Kimi K1.5 and Qwen3 don't publish scores on any of the same benchmarks.