Gemini 3.7 Flash vs Kimi K2.7 Code
Gemini 3.7 Flash leads the LLM Stats Score 50.9 to 39.6. Kimi K2.7 Code is 1.0x cheaper per token.
Google · Moonshot AI · Updated for 2026
Which is better?
Gemini 3.7 Flash leads the overall LLM Stats Score 50.9 to 39.6, ranking #13 overall.
In the 2 individual benchmarks reported for both models, Gemini 3.7 Flash wins 2; this is a narrower head-to-head signal than the composite indexes.
Gemini 3.7 Flash also accepts a larger context window (1,048,576 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 Gemini 3.7 Flash
- overall performance matters — it scores 50.9 and ranks #13 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Kimi K2.7 Code
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
18 reported for Gemini 3.7 Flash · 9 for Kimi K2.7 Code
Gemini 3.7 Flash outperforms in 2 benchmarks (DeepSWE 1.1, FrontierCode 1.1), while Kimi K2.7 Code is better at 0 benchmarks.
Gemini 3.7 Flash significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.7 Flash ($0.75/1M tokens) is 1.0x more expensive than Kimi K2.7 Code ($0.74/1M tokens).
For output processing, Gemini 3.7 Flash ($3.75/1M tokens) is 1.1x more expensive than Kimi K2.7 Code ($3.50/1M tokens).
In conclusion, Gemini 3.7 Flash 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
Gemini 3.7 Flash accepts 1,048,576 input tokens compared to Kimi K2.7 Code's 262,144 tokens. Kimi K2.7 Code can generate longer responses up to 131,072 tokens, while Gemini 3.7 Flash is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 3.7 Flash and Kimi K2.7 Code support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 3.7 Flash
Kimi K2.7 Code
License
Usage and distribution terms
Gemini 3.7 Flash is licensed under a proprietary license, 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.
Proprietary
Closed source
Modified MIT License
Open weights
Release Timeline
When each model was launched
Gemini 3.7 Flash was released on 2026-08-13, while Kimi K2.7 Code was released on 2026-06-12.
Gemini 3.7 Flash is 2 months newer than Kimi K2.7 Code.
Aug 13, 2026
2 weeks ago
2mo newerJun 12, 2026
2 months ago
Knowledge Cutoff
When training data ends
Gemini 3.7 Flash has a documented knowledge cutoff of 2026-03-31, while Kimi K2.7 Code's cutoff date is not specified.
We can confirm Gemini 3.7 Flash's training data extends to 2026-03-31, but cannot make a direct comparison without Kimi K2.7 Code's cutoff date.
Mar 2026
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Provider Availability
Gemini 3.7 Flash is available from Google. Kimi K2.7 Code is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
Gemini 3.7 Flash
Kimi K2.7 Code
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 3.7 Flash and Kimi K2.7 Code side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 3.7 Flash vs Kimi K2.7 Code.