Model Comparison

Gemini 3.5 Flash-Lite vs Kimi K2.7 CodeWhich is better in 2026?

Comparing Gemini 3.5 Flash-Lite and Kimi K2.7 Code across benchmarks, pricing, and capabilities.

Verdict: Gemini 3.5 Flash-Lite vs Kimi K2.7 Code — which is better?

Gemini 3.5 Flash-Lite (by Google) 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.

On price, Gemini 3.5 Flash-Lite is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 3.5 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemini 3.5 Flash-Lite if…

  • cost matters — it's about 1.7x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Jul 2026

Choose Kimi K2.7 Code if…

  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemini 3.5 Flash-Lite and Kimi K2.7 Codedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemini 3.5 Flash-Lite costs less

For input processing, Gemini 3.5 Flash-Lite ($0.30/1M tokens) is 2.5x cheaper than Kimi K2.7 Code ($0.74/1M tokens).

For output processing, Gemini 3.5 Flash-Lite ($2.50/1M tokens) is 1.4x cheaper than Kimi K2.7 Code ($3.50/1M tokens).

In conclusion, Kimi K2.7 Code is more expensive than Gemini 3.5 Flash-Lite.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Jul 28 2026 • llm-stats.com
Google
Gemini 3.5 Flash-Lite
Input tokens$0.30
Output tokens$2.50
Best providerGoogle
Moonshot AI
Kimi K2.7 Code
Input tokens$0.74
Output tokens$3.50
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite is limited to 65,536 tokens.

Google
Gemini 3.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
Moonshot AI
Kimi K2.7 Code
Input262,144 tokens
Output131,072 tokens
Tue Jul 28 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 3.5 Flash-Lite and Kimi K2.7 Code support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 3.5 Flash-Lite

Text
Images
Audio
Video

Kimi K2.7 Code

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3.5 Flash-Lite 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.

Gemini 3.5 Flash-Lite

Proprietary

Closed source

Kimi K2.7 Code

Modified MIT License

Open weights

Release Timeline

When each model was launched

Gemini 3.5 Flash-Lite was released on 2026-07-21, while Kimi K2.7 Code was released on 2026-06-12.

Gemini 3.5 Flash-Lite is 1 month newer than Kimi K2.7 Code.

Gemini 3.5 Flash-Lite

Jul 21, 2026

1 weeks ago

1mo newer
Kimi K2.7 Code

Jun 12, 2026

1 months ago

Knowledge Cutoff

When training data ends

Gemini 3.5 Flash-Lite has a documented knowledge cutoff of 2026-03-31, while Kimi K2.7 Code's cutoff date is not specified.

We can confirm Gemini 3.5 Flash-Lite's training data extends to 2026-03-31, but cannot make a direct comparison without Kimi K2.7 Code's cutoff date.

Gemini 3.5 Flash-Lite

Mar 2026

Kimi K2.7 Code

—

Provider Availability

Gemini 3.5 Flash-Lite is available from Google. Kimi K2.7 Code is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.

Gemini 3.5 Flash-Lite

google logo
Google
Input Price:Input: $0.30/1MOutput Price:Output: $2.50/1M

Kimi K2.7 Code

deepinfra logo
Deepinfra
Input Price:Input: $0.74/1MOutput Price:Output: $3.50/1M
fireworks logo
Fireworks
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
moonshot logo
Unknown Organization
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
novita logo
Novita
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
together logo
Together
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (1,048,576 tokens)
Less expensive input tokens
Less expensive output tokens
Moonshot AI
Has open weights

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemini 3.5 Flash-Lite and Kimi K2.7 Code side-by-side, then vote on the output you prefer.

Gemini 3.5 Flash-Lite
✓ Preferred
Kimi K2.7 Code
Open in Playground
AI Model Comparison Table
Feature
Google
Gemini 3.5 Flash-Lite
Moonshot AI
Kimi K2.7 Code

FAQ

Common questions about Gemini 3.5 Flash-Lite vs Kimi K2.7 Code.

Which is better, Gemini 3.5 Flash-Lite or Kimi K2.7 Code?

Gemini 3.5 Flash-Lite (Google) and Kimi K2.7 Code (Moonshot AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemini 3.5 Flash-Lite compare to Kimi K2.7 Code in benchmarks?

Gemini 3.5 Flash-Lite scores CharXiv-R: 76.5%, OSWorld-Verified: 74.0%, SWE-Bench Pro: 54.2%, Terminal-Bench 2.1: 54.0%, MLE-Bench: 39.2%. Kimi K2.7 Code scores MCP-Mark: 81.1%, MCP Atlas: 76.0%, LiveBench: 71.9%, Kimi Code Bench v2: 62.0%, Program Bench: 53.6%.

Is Gemini 3.5 Flash-Lite cheaper than Kimi K2.7 Code?

Gemini 3.5 Flash-Lite is 2.5x cheaper for input tokens. Gemini 3.5 Flash-Lite costs $0.30/M input and $2.50/M output via google. Kimi K2.7 Code costs $0.74/M input and $3.50/M output via deepinfra.

What are the context window sizes for Gemini 3.5 Flash-Lite and Kimi K2.7 Code?

Gemini 3.5 Flash-Lite supports 1.0M tokens and Kimi K2.7 Code supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 3.5 Flash-Lite and Kimi K2.7 Code?

Key differences include context window (1.0M vs 262K), input pricing ($0.30 vs $0.74/M), licensing (Proprietary vs Modified MIT License). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 3.5 Flash-Lite and Kimi K2.7 Code?

Gemini 3.5 Flash-Lite is developed by Google and Kimi K2.7 Code is developed by Moonshot AI.

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