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DeepSeek-V3 vs Gemini 2.0 Flash

DeepSeek-V3 and Gemini 2.0 Flash are closely matched at 16.0 and 16.5 on the LLM Stats Score. Gemini 2.0 Flash is 2.7x cheaper per token.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek-V3 and Gemini 2.0 Flash are closely matched on the overall LLM Stats Score at 16.0 and 16.5.

In the 3 individual benchmarks reported for both models, Gemini 2.0 Flash wins 2; this is a narrower head-to-head signal than the composite indexes.

On price, Gemini 2.0 Flash is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 2.0 Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose DeepSeek-V3

  • you want the most recent training data — it shipped Dec 2024
  • you need open weights you can self-host or fine-tune

Choose Gemini 2.0 Flash

  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results
  • cost matters — it's about 2.7x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window

At a glance

The differences that matter most.

DeepSeek-V3
DeepSeek
Gemini 2.0 Flash
Google
Core performance indexes
LLM Stats Score
16.0
#208
16.5
#203
Reasoning
15.0
#207
15.9
#202
Coding
6.5
#175
1.7
#212
Cost, coverage & limits
Benchmark wins
1 of 3
2 of 3
Input price
$0.27 / M
$0.10 / M
Output price
$1.10 / M
$0.40 / M
Context window
131,072
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3
Gemini 2.0 Flash
Math
18.1#172
23.4#119
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V3 · 13 for Gemini 2.0 Flash

3 shared

DeepSeek-V3 outperforms in 1 benchmarks (LiveCodeBench), while Gemini 2.0 Flash is better at 2 benchmarks (GPQA, MMLU-Pro).

Gemini 2.0 Flash shows notably better performance in the majority of benchmarks.

Sun Aug 30 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Gemini 2.0 Flash costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 2.7x more expensive than Gemini 2.0 Flash ($0.10/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 2.8x more expensive than Gemini 2.0 Flash ($0.40/1M tokens).

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

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

Lowest available price from all providers
Sun Aug 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Google
Gemini 2.0 Flash
Input tokens$0.10
Output tokens$0.40
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 2.0 Flash accepts 1,048,576 input tokens compared to DeepSeek-V3's 131,072 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Gemini 2.0 Flash is limited to 8,192 tokens.

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Google
Gemini 2.0 Flash
Input1,048,576 tokens
Output8,192 tokens
Sun Aug 30 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

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

DeepSeek-V3

Text
Images
Audio
Video

Gemini 2.0 Flash

Text
Images
Audio
Video

License

Usage and distribution terms

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

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Gemini 2.0 Flash

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Gemini 2.0 Flash was released on 2024-12-01.

DeepSeek-V3 is 1 month newer than Gemini 2.0 Flash.

DeepSeek-V3

Dec 25, 2024

1.7 years ago

3w newer
Gemini 2.0 Flash

Dec 1, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash has a documented knowledge cutoff of 2024-08-01, while DeepSeek-V3's cutoff date is not specified.

We can confirm Gemini 2.0 Flash's training data extends to 2024-08-01, but cannot make a direct comparison without DeepSeek-V3's cutoff date.

DeepSeek-V3

—

Gemini 2.0 Flash

Aug 2024

Provider Availability

DeepSeek-V3 is available from DeepSeek. Gemini 2.0 Flash is available from Google.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Gemini 2.0 Flash

google logo
Google
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3 and Gemini 2.0 Flash side-by-side, then vote on the output you prefer.

DeepSeek-V3
✓ Preferred
Gemini 2.0 Flash
Open in Playground

FAQ

Common questions about DeepSeek-V3 vs Gemini 2.0 Flash.

Which is better, DeepSeek-V3 or Gemini 2.0 Flash?

DeepSeek-V3 and Gemini 2.0 Flash are closely matched on the LLM Stats Score at 16.0 and 16.5. DeepSeek-V3 is made by DeepSeek and Gemini 2.0 Flash is made by Google. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V3 compare to Gemini 2.0 Flash in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Gemini 2.0 Flash scores Natural2Code: 92.9%, MATH: 89.7%, FACTS Grounding: 83.6%, MMLU-Pro: 76.4%, EgoSchema: 71.5%.

Is DeepSeek-V3 cheaper than Gemini 2.0 Flash?

Gemini 2.0 Flash is 2.7x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Gemini 2.0 Flash costs $0.10/M input and $0.40/M output via google.

What are the context window sizes for DeepSeek-V3 and Gemini 2.0 Flash?

DeepSeek-V3 supports 131K tokens and Gemini 2.0 Flash 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 and Gemini 2.0 Flash?

Key differences include LLM Stats Score (16.0 vs 16.5), context window (131K vs 1.0M), input pricing ($0.27 vs $0.10/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.

Who makes DeepSeek-V3 and Gemini 2.0 Flash?

DeepSeek-V3 is developed by DeepSeek and Gemini 2.0 Flash is developed by Google.

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