Model Comparison

DeepSeek-V3.2 (Non-thinking) vs Gemini 1.5 Flash 8B

Comparing DeepSeek-V3.2 (Non-thinking) and Gemini 1.5 Flash 8B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2 (Non-thinking) and Gemini 1.5 Flash 8B don'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 1.5 Flash 8B costs less

For input processing, DeepSeek-V3.2 (Non-thinking) ($0.28/1M tokens) is 4.0x more expensive than Gemini 1.5 Flash 8B ($0.07/1M tokens).

For output processing, DeepSeek-V3.2 (Non-thinking) ($0.42/1M tokens) is 1.4x more expensive than Gemini 1.5 Flash 8B ($0.30/1M tokens).

In conclusion, DeepSeek-V3.2 (Non-thinking) is more expensive than Gemini 1.5 Flash 8B.*

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

Lowest available price from all providers
Tue May 26 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Google
Gemini 1.5 Flash 8B
Input tokens$0.07
Output tokens$0.30
Best providerGoogle
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Model Size

Parameter count comparison

677.0B diff

DeepSeek-V3.2 (Non-thinking) has 677.0B more parameters than Gemini 1.5 Flash 8B, making it 8462.5% larger.

DeepSeek
DeepSeek-V3.2 (Non-thinking)
685.0Bparameters
Google
Gemini 1.5 Flash 8B
8.0Bparameters
685.0B
DeepSeek-V3.2 (Non-thinking)
8.0B
Gemini 1.5 Flash 8B

Context Window

Maximum input and output token capacity

Gemini 1.5 Flash 8B accepts 1,048,576 input tokens compared to DeepSeek-V3.2 (Non-thinking)'s 131,072 tokens. Both models can generate responses up to 8,192 tokens.

DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input131,072 tokens
Output8,192 tokens
Google
Gemini 1.5 Flash 8B
Input1,048,576 tokens
Output8,192 tokens
Tue May 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 1.5 Flash 8B supports multimodal inputs, whereas DeepSeek-V3.2 (Non-thinking) does not.

Gemini 1.5 Flash 8B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2 (Non-thinking)

Text
Images
Audio
Video

Gemini 1.5 Flash 8B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2 (Non-thinking) is licensed under MIT, while Gemini 1.5 Flash 8B 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 1.5 Flash 8B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while Gemini 1.5 Flash 8B was released on 2024-03-15.

DeepSeek-V3.2 (Non-thinking) is 21 months newer than Gemini 1.5 Flash 8B.

DeepSeek-V3.2 (Non-thinking)

Dec 1, 2025

5 months ago

1.7yr newer
Gemini 1.5 Flash 8B

Mar 15, 2024

2.2 years ago

Knowledge Cutoff

When training data ends

Gemini 1.5 Flash 8B has a documented knowledge cutoff of 2024-10-01, while DeepSeek-V3.2 (Non-thinking)'s cutoff date is not specified.

We can confirm Gemini 1.5 Flash 8B's training data extends to 2024-10-01, but cannot make a direct comparison without DeepSeek-V3.2 (Non-thinking)'s cutoff date.

DeepSeek-V3.2 (Non-thinking)

—

Gemini 1.5 Flash 8B

Oct 2024

Provider Availability

DeepSeek-V3.2 (Non-thinking) is available from DeepSeek. Gemini 1.5 Flash 8B is available from Google.

DeepSeek-V3.2 (Non-thinking)

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

Gemini 1.5 Flash 8B

google logo
Google
Input Price:Input: $0.07/1MOutput Price:Output: $0.30/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Has open weights
Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
DeepSeekDeepSeek-V3.2 (Non-thinking)
GoogleGemini 1.5 Flash 8B
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Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Non-thinking)
Google
Gemini 1.5 Flash 8B

FAQ

Common questions about DeepSeek-V3.2 (Non-thinking) vs Gemini 1.5 Flash 8B.

Which is better, DeepSeek-V3.2 (Non-thinking) or Gemini 1.5 Flash 8B?

DeepSeek-V3.2 (Non-thinking) (DeepSeek) and Gemini 1.5 Flash 8B (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 1.5 Flash 8B in benchmarks?

Gemini 1.5 Flash 8B scores XSTest: 92.6%, FLEURS: 86.4%, Natural2Code: 75.5%, WMT23: 72.6%, Video-MME: 66.2%.

Is DeepSeek-V3.2 (Non-thinking) cheaper than Gemini 1.5 Flash 8B?

Gemini 1.5 Flash 8B is 4.0x cheaper for input tokens. DeepSeek-V3.2 (Non-thinking) costs $0.28/M input and $0.42/M output via deepseek. Gemini 1.5 Flash 8B costs $0.07/M input and $0.30/M output via google.

What are the context window sizes for DeepSeek-V3.2 (Non-thinking) and Gemini 1.5 Flash 8B?

DeepSeek-V3.2 (Non-thinking) supports 131K tokens and Gemini 1.5 Flash 8B supports 1.0M 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 1.5 Flash 8B?

Key differences include context window (131K vs 1.0M), input pricing ($0.28 vs $0.07/M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Non-thinking) and Gemini 1.5 Flash 8B?

DeepSeek-V3.2 (Non-thinking) is developed by DeepSeek and Gemini 1.5 Flash 8B is developed by Google.