Model comparison
Qwen3.5 vs Kimi K2.5
- Input
- $0.54 / 1M tokens
- Output
- $3.40 / 1M tokens
- Context
- 256K
- Released
- 2026-02-16
- Input
- $0.60 / 1M tokens
- Output
- $2.50 / 1M tokens
- Context
- 256K
- Released
- 2026-01-27
Qwen3.5 scores higher on 4 of the 6 benchmarks both models report (the other leads on 2); Qwen3.5 is cheaper on input tokens ($0.5 vs $0.6 per 1M, 1.1×).
Specs and pricing side by side
| Spec | Qwen3.5 | Kimi K2.5 |
|---|---|---|
| Maker | Alibaba (Qwen) | Moonshot AI (Kimi) |
| Released | 2026-02-16 | 2026-01-27 |
| Context window | 256K | 256Ksame |
| Max output | not published | 16K |
| Input price | $0.54 / 1M tokens | $0.60 / 1M tokens |
| Output price | $3.40 / 1M tokens | $2.50 / 1M tokens |
| Parameters | 397B total / 17B active (MoE, 512 experts) | 1T total, 32B active (MoE) |
| License | Apache-2.0 | Modified MIT License |
| Weights | Open weights | Open weightssame |
| Modalities | Text, Vision, Video, PDF | Text, Vision, Video |
Not published by either maker: knowledge cutoff.
Benchmarks both models report
| Benchmark | Qwen3.5 | Kimi K2.5 |
|---|---|---|
| GPQA Diamond | 88.4% | 87.6% |
| LiveCodeBench v6 | 83.6% | 85% |
| SWE-bench Verified | 76.4% | 76.8% |
| MMLU-Pro | 87.8% | 87.1% |
| MMMU-Pro | 79% | 78.5% |
| Terminal-Bench 2.0 | 52.5% | 50.8% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Qwen3.5 if…
- You care about GPQA Diamond, MMLU-Pro, MMMU-Pro (it scores higher on 4 shared benchmarks).
- Cost matters: input tokens cost 1.1× less ($0.5 vs $0.6 per 1M).
- You need PDF input, which Kimi K2.5 lacks.
- Your use case is: self-hosted agentic systems that need open weights for tool use, browsing, and terminal/coding workflows.
Pick Kimi K2.5 if…
- You care about LiveCodeBench v6, SWE-bench Verified (it scores higher on 2 shared benchmarks).
- Your use case is: agentic software engineering: multi-file bug fixes, refactors, and repo-level tasks.
FAQ
Which is better, Qwen3.5 or Kimi K2.5?
Qwen3.5 scores higher on 4 of the 6 benchmarks both models report (the other leads on 2); Qwen3.5 is cheaper on input tokens ($0.5 vs $0.6 per 1M, 1.1×). The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is Qwen3.5?
Qwen3.5: $0.54 / 1M tokens input, $3.40 / 1M tokens output. Kimi K2.5: $0.60 / 1M tokens input, $2.50 / 1M tokens output (list API prices as published by each maker).
What are the context windows of Qwen3.5 and Kimi K2.5?
Qwen3.5 offers 256K; Kimi K2.5 offers 256K with up to 16K output.
Is Qwen3.5 newer than Kimi K2.5?
Qwen3.5 was released 2026-02-16; Kimi K2.5 was released 2026-01-27.