DeepSeek-V3.2 (Thinking) vs Gemini 2.5 Pro Preview 06-05 Comparison

Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

DeepSeek-V3.2 (Thinking) outperforms in 4 benchmarks (AIME 2025, Humanity's Last Exam, LiveCodeBench, SWE-Bench Verified), while Gemini 2.5 Pro Preview 06-05 is better at 1 benchmark (GPQA).

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

Tue Mar 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2 (Thinking) costs less

For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 4.5x cheaper than Gemini 2.5 Pro Preview 06-05 ($1.25/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 23.8x cheaper than Gemini 2.5 Pro Preview 06-05 ($10.00/1M tokens).

In conclusion, Gemini 2.5 Pro Preview 06-05 is more expensive than DeepSeek-V3.2 (Thinking).*

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

Lowest available price from all providers
Tue Mar 17 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Google
Gemini 2.5 Pro Preview 06-05
Input tokens$1.25
Output tokens$10.00
Best providerGoogle
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Context Window

Maximum input and output token capacity

Gemini 2.5 Pro Preview 06-05 accepts 1,048,576 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. DeepSeek-V3.2 (Thinking) can generate longer responses up to 65,536 tokens, while Gemini 2.5 Pro Preview 06-05 is limited to 65,535 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Google
Gemini 2.5 Pro Preview 06-05
Input1,048,576 tokens
Output65,535 tokens
Tue Mar 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.5 Pro Preview 06-05 supports multimodal inputs, whereas DeepSeek-V3.2 (Thinking) does not.

Gemini 2.5 Pro Preview 06-05 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2 (Thinking)

Text
Images
Audio
Video

Gemini 2.5 Pro Preview 06-05

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while Gemini 2.5 Pro Preview 06-05 uses a proprietary license.

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

DeepSeek-V3.2 (Thinking)

MIT

Open weights

Gemini 2.5 Pro Preview 06-05

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while Gemini 2.5 Pro Preview 06-05 was released on 2025-06-05.

DeepSeek-V3.2 (Thinking) is 6 months newer than Gemini 2.5 Pro Preview 06-05.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

3 months ago

5mo newer
Gemini 2.5 Pro Preview 06-05

Jun 5, 2025

9 months ago

Knowledge Cutoff

When training data ends

Gemini 2.5 Pro Preview 06-05 has a documented knowledge cutoff of 2025-01-31, while DeepSeek-V3.2 (Thinking)'s cutoff date is not specified.

We can confirm Gemini 2.5 Pro Preview 06-05's training data extends to 2025-01-31, but cannot make a direct comparison without DeepSeek-V3.2 (Thinking)'s cutoff date.

DeepSeek-V3.2 (Thinking)

Gemini 2.5 Pro Preview 06-05

Jan 2025

Provider Availability

DeepSeek-V3.2 (Thinking) is available from DeepSeek. Gemini 2.5 Pro Preview 06-05 is available from Google. The availability of providers can affect quality of the model and reliability.

DeepSeek-V3.2 (Thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

Gemini 2.5 Pro Preview 06-05

google logo
Google
Input Price:Input: $1.25/1MOutput Price:Output: $10.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Less expensive input tokens
Less expensive output tokens
Has open weights
Higher AIME 2025 score (93.1% vs 88.0%)
Higher Humanity's Last Exam score (25.1% vs 21.6%)
Higher LiveCodeBench score (83.3% vs 69.0%)
Higher SWE-Bench Verified score (73.1% vs 67.2%)
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Higher GPQA score (86.4% vs 82.4%)

Detailed Comparison