Kimi K2.7 Code vs Qwen3.7 Max
Kimi K2.7 Code and Qwen3.7 Max are closely matched at 39.1 and 45.6 on the LLM Stats Score. Kimi K2.7 Code is 1.4x cheaper per token.
Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Kimi K2.7 Code and Qwen3.7 Max are closely matched on the overall LLM Stats Score at 39.1 and 45.6.
In the 3 individual benchmarks reported for both models, Qwen3.7 Max wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Kimi K2.7 Code is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.7 Max also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Kimi K2.7 Code
- cost matters — it's about 1.4x cheaper per token
- you want the most recent training data — it shipped Jun 2026
- you need open weights you can self-host or fine-tune
Choose Qwen3.7 Max
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you process long inputs — it offers a 1,000,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for Kimi K2.7 Code · 42 for Qwen3.7 Max
Kimi K2.7 Code outperforms in 1 benchmarks (MCP-Mark), while Qwen3.7 Max is better at 2 benchmarks (LiveBench, MCP Atlas).
Qwen3.7 Max shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2.7 Code ($0.68/1M tokens) is 1.8x cheaper than Qwen3.7 Max ($1.25/1M tokens).
For output processing, Kimi K2.7 Code ($3.40/1M tokens) is 1.1x cheaper than Qwen3.7 Max ($3.75/1M tokens).
In conclusion, Qwen3.7 Max is more expensive than Kimi K2.7 Code.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3.7 Max accepts 1,000,000 input tokens compared to Kimi K2.7 Code's 262,144 tokens. Kimi K2.7 Code can generate longer responses up to 262,144 tokens, while Qwen3.7 Max is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Kimi K2.7 Code supports multimodal inputs, whereas Qwen3.7 Max does not.
Kimi K2.7 Code can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2.7 Code
Qwen3.7 Max
License
Usage and distribution terms
Kimi K2.7 Code is licensed under Modified MIT License, while Qwen3.7 Max uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Modified MIT License
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Kimi K2.7 Code was released on 2026-06-12, while Qwen3.7 Max was released on 2026-05-19.
Kimi K2.7 Code is 1 month newer than Qwen3.7 Max.
Jun 12, 2026
2 months ago
3w newerMay 19, 2026
3 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K2.7 Code is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together. Qwen3.7 Max is available from Novita, DeepInfra, Together.
Kimi K2.7 Code
Qwen3.7 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.7 Code and Qwen3.7 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.7 Code vs Qwen3.7 Max.