Model Comparison

DeepSeek-V3.1 vs Gemini 2.5 Flash-Lite

DeepSeek-V3.1 significantly outperforms across most benchmarks. Gemini 2.5 Flash-Lite is 2.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

DeepSeek-V3.1 outperforms in 6 benchmarks (Aider-Polyglot, GPQA, Humanity's Last Exam, LiveCodeBench, SimpleQA, SWE-Bench Verified), while Gemini 2.5 Flash-Lite is better at 0 benchmarks.

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Mon May 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemini 2.5 Flash-Lite costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 2.7x more expensive than Gemini 2.5 Flash-Lite ($0.10/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 2.5x more expensive than Gemini 2.5 Flash-Lite ($0.40/1M tokens).

In conclusion, DeepSeek-V3.1 is more expensive than Gemini 2.5 Flash-Lite.*

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

Lowest available price from all providers

Mon May 25 2026 • llm-stats.com

DeepSeek-V3.1

Input tokens$0.27

Output tokens$1.00

Best providerDeepinfra

Gemini 2.5 Flash-Lite

Input tokens$0.10

Output tokens$0.40

Best providerGoogle

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Context Window

Maximum input and output token capacity

Gemini 2.5 Flash-Lite accepts 1,048,576 input tokens compared to DeepSeek-V3.1's 163,840 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while Gemini 2.5 Flash-Lite is limited to 65,536 tokens.

DeepSeek-V3.1

Input163,840 tokens

Output163,840 tokens

Gemini 2.5 Flash-Lite

Input1,048,576 tokens

Output65,536 tokens

Mon May 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.5 Flash-Lite supports multimodal inputs, whereas DeepSeek-V3.1 does not.

Gemini 2.5 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.1

Text

Images

Audio

Video

Gemini 2.5 Flash-Lite

Text

Images

Audio

Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while Gemini 2.5 Flash-Lite uses Creative Commons Attribution 4.0 License.

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

DeepSeek-V3.1

MIT

Open weights

Gemini 2.5 Flash-Lite

Creative Commons Attribution 4.0 License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Gemini 2.5 Flash-Lite was released on 2025-06-17.

Gemini 2.5 Flash-Lite is 5 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.4 years ago

Gemini 2.5 Flash-Lite

Jun 17, 2025

11 months ago

5mo newer

Knowledge Cutoff

When training data ends

Gemini 2.5 Flash-Lite has a documented knowledge cutoff of 2025-01-01, while DeepSeek-V3.1's cutoff date is not specified.

We can confirm Gemini 2.5 Flash-Lite's training data extends to 2025-01-01, but cannot make a direct comparison without DeepSeek-V3.1's cutoff date.

DeepSeek-V3.1

—

Gemini 2.5 Flash-Lite

Jan 2025

Provider Availability

DeepSeek-V3.1 is available from DeepInfra, Novita. Gemini 2.5 Flash-Lite is available from Google.

DeepSeek-V3.1

Deepinfra

Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

Novita

Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

Gemini 2.5 Flash-Lite

Google

Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek-V3.1

View details

DeepSeek

Higher Aider-Polyglot score (68.4% vs 26.7%)

Higher GPQA score (74.9% vs 64.6%)

Higher Humanity's Last Exam score (15.9% vs 5.1%)

Higher LiveCodeBench score (56.4% vs 33.7%)

Higher SimpleQA score (93.4% vs 10.7%)

Higher SWE-Bench Verified score (66.0% vs 31.6%)

Gemini 2.5 Flash-Lite

View details

Google

Larger context window (1,048,576 tokens)

Supports multimodal inputs

Less expensive input tokens

Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek-V3.1	Gemini 2.5 Flash-Lite

FAQ

Common questions about DeepSeek-V3.1 vs Gemini 2.5 Flash-Lite.

Which is better, DeepSeek-V3.1 or Gemini 2.5 Flash-Lite?

DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek-V3.1 is made by DeepSeek and Gemini 2.5 Flash-Lite is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.1 compare to Gemini 2.5 Flash-Lite in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Gemini 2.5 Flash-Lite scores FACTS Grounding: 84.1%, Global-MMLU-Lite: 81.1%, MMMU: 72.9%, GPQA: 64.6%, Vibe-Eval: 51.3%.

Is DeepSeek-V3.1 cheaper than Gemini 2.5 Flash-Lite?

Gemini 2.5 Flash-Lite is 2.7x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. Gemini 2.5 Flash-Lite costs $0.10/M input and $0.40/M output via google.

What are the context window sizes for DeepSeek-V3.1 and Gemini 2.5 Flash-Lite?

DeepSeek-V3.1 supports 164K tokens and Gemini 2.5 Flash-Lite 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-V3.1 and Gemini 2.5 Flash-Lite?

Key differences include context window (164K vs 1.0M), input pricing ($0.27 vs $0.10/M), multimodal support (no vs yes), licensing (MIT vs Creative Commons Attribution 4.0 License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.1 and Gemini 2.5 Flash-Lite?

DeepSeek-V3.1 is developed by DeepSeek and Gemini 2.5 Flash-Lite is developed by Google.