Model Comparison

DeepSeek-V3 0324 vs Gemini 2.0 Flash-Lite

DeepSeek-V3 0324 significantly outperforms across most benchmarks. Gemini 2.0 Flash-Lite is 3.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3 0324 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Gemini 2.0 Flash-Lite is better at 0 benchmarks.

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Thu Apr 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemini 2.0 Flash-Lite costs less

For input processing, DeepSeek-V3 0324 ($0.28/1M tokens) is 4.0x more expensive than Gemini 2.0 Flash-Lite ($0.07/1M tokens).

For output processing, DeepSeek-V3 0324 ($1.14/1M tokens) is 3.8x more expensive than Gemini 2.0 Flash-Lite ($0.30/1M tokens).

In conclusion, DeepSeek-V3 0324 is more expensive than Gemini 2.0 Flash-Lite.*

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

Lowest available price from all providers
Thu Apr 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3 0324
Input tokens$0.28
Output tokens$1.14
Best providerNovita
Google
Gemini 2.0 Flash-Lite
Input tokens$0.07
Output tokens$0.30
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 2.0 Flash-Lite accepts 1,048,576 input tokens compared to DeepSeek-V3 0324's 163,840 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 tokens, while Gemini 2.0 Flash-Lite is limited to 8,192 tokens.

DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Google
Gemini 2.0 Flash-Lite
Input1,048,576 tokens
Output8,192 tokens
Thu Apr 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 2.0 Flash-Lite supports multimodal inputs, whereas DeepSeek-V3 0324 does not.

Gemini 2.0 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3 0324

Text
Images
Audio
Video

Gemini 2.0 Flash-Lite

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while Gemini 2.0 Flash-Lite uses a proprietary license.

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

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Gemini 2.0 Flash-Lite

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3 0324 was released on 2025-03-25, while Gemini 2.0 Flash-Lite was released on 2025-02-05.

DeepSeek-V3 0324 is 2 months newer than Gemini 2.0 Flash-Lite.

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

1mo newer
Gemini 2.0 Flash-Lite

Feb 5, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash-Lite has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V3 0324's cutoff date is not specified.

We can confirm Gemini 2.0 Flash-Lite's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-V3 0324's cutoff date.

DeepSeek-V3 0324

—

Gemini 2.0 Flash-Lite

Jun 2024

Provider Availability

DeepSeek-V3 0324 is available from Novita. Gemini 2.0 Flash-Lite is available from Google.

DeepSeek-V3 0324

novita logo
Novita
Input Price:Input: $0.28/1MOutput Price:Output: $1.14/1M

Gemini 2.0 Flash-Lite

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
Higher GPQA score (68.4% vs 51.5%)
Higher MMLU-Pro score (81.2% vs 71.6%)
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
DeepSeek-V3 0324
Google
Gemini 2.0 Flash-Lite

FAQ

Common questions about DeepSeek-V3 0324 vs Gemini 2.0 Flash-Lite

DeepSeek-V3 0324 significantly outperforms across most benchmarks. DeepSeek-V3 0324 is made by DeepSeek and Gemini 2.0 Flash-Lite is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%. Gemini 2.0 Flash-Lite scores MATH: 86.8%, FACTS Grounding: 83.6%, Global-MMLU-Lite: 78.2%, MMLU-Pro: 71.6%, MMMU: 68.0%.
Gemini 2.0 Flash-Lite is 4.0x cheaper for input tokens. DeepSeek-V3 0324 costs $0.28/M input and $1.14/M output via novita. Gemini 2.0 Flash-Lite costs $0.07/M input and $0.30/M output via google.
DeepSeek-V3 0324 supports 164K tokens and Gemini 2.0 Flash-Lite supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (164K vs 1.0M), input pricing ($0.28 vs $0.07/M), multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 0324 is developed by DeepSeek and Gemini 2.0 Flash-Lite is developed by Google.