Model Comparison

DiffusionGemma 26B-A4B vs Kimi K2.7 CodeWhich is better in 2026?

Comparing DiffusionGemma 26B-A4B and Kimi K2.7 Code across benchmarks, pricing, and capabilities.

Verdict: DiffusionGemma 26B-A4B vs Kimi K2.7 Code — which is better?

DiffusionGemma 26B-A4B (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.

Choose DiffusionGemma 26B-A4B if…

  • you are already invested in the Google ecosystem

Choose Kimi K2.7 Code if…

  • you want the most recent training data — it shipped Jun 2026

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DiffusionGemma 26B-A4B 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

Model Size

Parameter count comparison

974.8B diff

Kimi K2.7 Code has 974.8B more parameters than DiffusionGemma 26B-A4B, making it 3868.3% larger.

Google
DiffusionGemma 26B-A4B
25.2Bparameters
Moonshot AI
Kimi K2.7 Code
1.0Tparameters
25.2B
DiffusionGemma 26B-A4B
1000.0B
Kimi K2.7 Code

Context Window

Maximum input and output token capacity

Only Kimi K2.7 Code specifies input context (262,144 tokens). Only Kimi K2.7 Code specifies output context (131,072 tokens).

Google
DiffusionGemma 26B-A4B
Input- tokens
Output- tokens
Moonshot AI
Kimi K2.7 Code
Input262,144 tokens
Output131,072 tokens
Fri Jul 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DiffusionGemma 26B-A4B and Kimi K2.7 Code support multimodal inputs.

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

DiffusionGemma 26B-A4B

Text
Images
Audio
Video

Kimi K2.7 Code

Text
Images
Audio
Video

License

Usage and distribution terms

DiffusionGemma 26B-A4B 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.

DiffusionGemma 26B-A4B

Apache 2.0

Open weights

Kimi K2.7 Code

Modified MIT License

Open weights

Release Timeline

When each model was launched

DiffusionGemma 26B-A4B was released on 2026-06-10, while Kimi K2.7 Code was released on 2026-06-12.

Kimi K2.7 Code is 0 month newer than DiffusionGemma 26B-A4B.

DiffusionGemma 26B-A4B

Jun 10, 2026

1 months ago

Kimi K2.7 Code

Jun 12, 2026

1 months ago

2d newer

Knowledge Cutoff

When training data ends

DiffusionGemma 26B-A4B has a documented knowledge cutoff of 2025-01-01, while Kimi K2.7 Code's cutoff date is not specified.

We can confirm DiffusionGemma 26B-A4B's training data extends to 2025-01-01, but cannot make a direct comparison without Kimi K2.7 Code's cutoff date.

DiffusionGemma 26B-A4B

Jan 2025

Kimi K2.7 Code

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google

No standout differentiators in the data we have for this pair.

Moonshot AI
Larger context window (262,144 tokens)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DiffusionGemma 26B-A4B and Kimi K2.7 Code side-by-side, then vote on the output you prefer.

DiffusionGemma 26B-A4B
✓ Preferred
Kimi K2.7 Code
Open in Playground
AI Model Comparison Table
Feature
Google
DiffusionGemma 26B-A4B
Moonshot AI
Kimi K2.7 Code

FAQ

Common questions about DiffusionGemma 26B-A4B vs Kimi K2.7 Code.

Which is better, DiffusionGemma 26B-A4B or Kimi K2.7 Code?

DiffusionGemma 26B-A4B (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 DiffusionGemma 26B-A4B compare to Kimi K2.7 Code in benchmarks?

DiffusionGemma 26B-A4B scores MMMLU: 81.5%, MMLU-Pro: 77.6%, GPQA: 73.2%, MathVision: 70.5%, AIME 2026: 69.1%. 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%.

What are the context window sizes for DiffusionGemma 26B-A4B and Kimi K2.7 Code?

DiffusionGemma 26B-A4B supports an unknown number of 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 DiffusionGemma 26B-A4B and Kimi K2.7 Code?

Key differences include licensing (Apache 2.0 vs Modified MIT License). See the full comparison above for benchmark-by-benchmark results.

Who makes DiffusionGemma 26B-A4B and Kimi K2.7 Code?

DiffusionGemma 26B-A4B is developed by Google and Kimi K2.7 Code is developed by Moonshot AI.

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