Model Comparison
Qwen3.5-397B-A17B vs Kimi K2.7 CodeWhich is better in 2026?
Kimi K2.7 Code significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is 1.3x cheaper per token.
Verdict: Qwen3.5-397B-A17B vs Kimi K2.7 Code — which is better?
Qwen3.5-397B-A17B (by Alibaba Cloud / Qwen Team) and Kimi K2.7 Code (by Moonshot AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Qwen3.5-397B-A17B outperforms in 0 benchmarks, while Kimi K2.7 Code is better at 1 benchmark (MCP-Mark). Kimi K2.7 Code significantly outperforms across most benchmarks.
On price, Qwen3.5-397B-A17B is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Qwen3.5-397B-A17B if…
- cost matters — it's about 1.3x cheaper per token
Choose Kimi K2.7 Code if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you want the most recent training data — it shipped Jun 2026
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.5-397B-A17B outperforms in 0 benchmarks, while Kimi K2.7 Code is better at 1 benchmark (MCP-Mark).
Kimi K2.7 Code significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen3.5-397B-A17B ($0.60/1M tokens) is 1.6x cheaper than Kimi K2.7 Code ($0.95/1M tokens).
For output processing, Qwen3.5-397B-A17B ($3.60/1M tokens) is 1.1x cheaper than Kimi K2.7 Code ($4.00/1M tokens).
In conclusion, Kimi K2.7 Code is more expensive than Qwen3.5-397B-A17B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2.7 Code has 603.0B more parameters than Qwen3.5-397B-A17B, making it 151.9% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 262,144 tokens. Kimi K2.7 Code can generate longer responses up to 262,144 tokens, while Qwen3.5-397B-A17B is limited to 64,000 tokens.
Input Capabilities
Supported data types and modalities
Both Qwen3.5-397B-A17B and Kimi K2.7 Code support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3.5-397B-A17B
Kimi K2.7 Code
License
Usage and distribution terms
Qwen3.5-397B-A17B is licensed under Apache 2.0, while Kimi K2.7 Code uses Modified MIT License.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Modified MIT License
Open weights
Release Timeline
When each model was launched
Qwen3.5-397B-A17B was released on 2026-02-16, while Kimi K2.7 Code was released on 2026-06-12.
Kimi K2.7 Code is 4 months newer than Qwen3.5-397B-A17B.
Feb 16, 2026
3 months ago
Jun 12, 2026
1 days ago
3mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Qwen3.5-397B-A17B is available from Novita. Kimi K2.7 Code is available from Moonshot AI, Novita.
Qwen3.5-397B-A17B
Kimi K2.7 Code
Outputs Comparison
Key Takeaways
Qwen3.5-397B-A17B
View detailsAlibaba Cloud / Qwen Team
Kimi K2.7 Code
View detailsMoonshot AI
Detailed Comparison
| Feature | | |
|---|
FAQ
Common questions about Qwen3.5-397B-A17B vs Kimi K2.7 Code.