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DeepSeek-V3.2 (Non-thinking) vs Gemini Diffusion

Comparing DeepSeek-V3.2 (Non-thinking) and Gemini Diffusion across benchmarks, pricing, and capabilities.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V3.2 (Non-thinking) and Gemini Diffusion trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V3.2 (Non-thinking)

  • you want the most recent training data — it shipped Dec 2025
  • you need open weights you can self-host or fine-tune

Choose Gemini Diffusion

  • you are already invested in the Google ecosystem

At a glance

The differences that matter most.

DeepSeek-V3.2 (Non-thinking)
DeepSeek
Gemini Diffusion
Google
Benchmark wins
—
—
Input price
$0.28 / M
— / M
Output price
$0.42 / M
— / M
Context window
131,072
—

Individual benchmarks

0 reported for DeepSeek-V3.2 (Non-thinking) · 10 for Gemini Diffusion

No common benchmarks found

DeepSeek-V3.2 (Non-thinking) and Gemini Diffusiondon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2 (Non-thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Non-thinking) specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input131,072 tokens
Output8,192 tokens
Google
Gemini Diffusion
Input- tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2 (Non-thinking) is licensed under MIT, while Gemini Diffusion uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3.2 (Non-thinking)

MIT

Open weights

Gemini Diffusion

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while Gemini Diffusion was released on 2025-05-20.

DeepSeek-V3.2 (Non-thinking) is 7 months newer than Gemini Diffusion.

DeepSeek-V3.2 (Non-thinking)

Dec 1, 2025

9 months ago

6mo newer
Gemini Diffusion

May 20, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3.2 (Non-thinking) and Gemini Diffusion side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Non-thinking)
✓ Preferred
Gemini Diffusion
Open in Playground

FAQ

Common questions about DeepSeek-V3.2 (Non-thinking) vs Gemini Diffusion.

Which is better, DeepSeek-V3.2 (Non-thinking) or Gemini Diffusion?

DeepSeek-V3.2 (Non-thinking) (DeepSeek) and Gemini Diffusion (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V3.2 (Non-thinking) compare to Gemini Diffusion in benchmarks?

Gemini Diffusion scores HumanEval: 89.6%, MBPP: 76.0%, Global-MMLU-Lite: 69.1%, LBPP (v2): 56.8%, BigCodeBench: 45.4%.

What are the context window sizes for DeepSeek-V3.2 (Non-thinking) and Gemini Diffusion?

DeepSeek-V3.2 (Non-thinking) supports 131K tokens and Gemini Diffusion supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2 (Non-thinking) and Gemini Diffusion?

Key differences include licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Non-thinking) and Gemini Diffusion?

DeepSeek-V3.2 (Non-thinking) is developed by DeepSeek and Gemini Diffusion is developed by Google.

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