Qwen vs Kimi at a glance
| Qwen | Kimi | |
|---|---|---|
| Developer | Alibaba | Moonshot AI |
| Latest version | Qwen3.7 Max | Kimi K3 |
| Known for | Multilingual | Long-context |
| Context window | Up to 1 million tokens | Up to 1 million tokens |
| Multimodal support | Text, images, and video | Text, images, and video |
| Open source | Yes | Partially |
| Official pricing | Free to chat here; low-cost API from $0.10 per million tokens | Free to chat here; API from $0.30 per million cached tokens |
Qwen benchmark highlight
Scores 80.4% on SWE-bench Verified and 92.4% on GPQA Diamond, the top-ranked Chinese model
Kimi benchmark highlight
Ranked #1 on LMArena's Frontend Code Arena, ahead of GPT and Claude on that leaderboard
Which one should you use?
Choose Qwen if you want:
- Multilingual & translation tasks
- Global/localization use cases
- Developers building on open models
- Long-running agent workflows
Choose Kimi if you want:
- Large document analysis
- Long-context research
- Cost-efficient agentic tasks
- Processing books & lengthy reports
Standout strengths
Qwen
200+ languages
Supports an unusually wide range of languages and dialects for global and localization work.
Native multimodal
Understands text, images, and video together within a single model, not bolted-on separately.
Massive open ecosystem
The most-downloaded open model family in the world, with a huge library of community fine-tunes.
Kimi
1M-token context window
Reads entire books, research papers, or codebases in a single pass without losing track.
Fast decoding at scale
A hybrid attention mechanism keeps long-context responses fast instead of slowing to a crawl.
Native vision understanding
Combines strong vision and language understanding in one model, not a separate add-on.
Frequently asked questions
Try Qwen and Kimi for free
No credit card, no account required. Pick Qwen for multilingual & translation tasks, or Kimi for large document analysis.