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DeepSeek R1 Distill Llama 70B vs Gemini 2.0 Flash Thinking

DeepSeek R1 Distill Llama 70B and Gemini 2.0 Flash Thinking are closely matched at 14.5 and 16.7 on the LLM Stats Score.

DeepSeek · Google · Updated for 2026

Which is better?

DeepSeek R1 Distill Llama 70B and Gemini 2.0 Flash Thinking are closely matched on the overall LLM Stats Score at 14.5 and 16.7.

The models split the 2 individual benchmarks reported for both models evenly.

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

Choose DeepSeek R1 Distill Llama 70B

  • you need open weights you can self-host or fine-tune

Choose Gemini 2.0 Flash Thinking

  • you want the most recent training data — it shipped Jan 2025

At a glance

The differences that matter most.

Core performance indexes
14.5
#234
16.7
#218
14.7
#227
17.0
#211
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
128,000

Individual benchmarks

4 reported for DeepSeek R1 Distill Llama 70B · 3 for Gemini 2.0 Flash Thinking

2 shared

DeepSeek R1 Distill Llama 70B outperforms in 1 benchmarks (AIME 2024), while Gemini 2.0 Flash Thinking is better at 1 benchmark (GPQA).

Both models are evenly matched across the benchmarks.

Fri Sep 11 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only DeepSeek R1 Distill Llama 70B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Llama 70B specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
Google
Gemini 2.0 Flash Thinking
Input- tokens
Output- tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 2.0 Flash Thinking supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.

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

DeepSeek R1 Distill Llama 70B

Text
Images
Audio
Video

Gemini 2.0 Flash Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Llama 70B is licensed under MIT, while Gemini 2.0 Flash Thinking uses a proprietary license.

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

DeepSeek R1 Distill Llama 70B

MIT

Open weights

Gemini 2.0 Flash Thinking

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Gemini 2.0 Flash Thinking was released on 2025-01-21.

Gemini 2.0 Flash Thinking is 0 month newer than DeepSeek R1 Distill Llama 70B.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.6 years ago

Gemini 2.0 Flash Thinking

Jan 21, 2025

1.6 years ago

1d newer

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash Thinking has a documented knowledge cutoff of 2024-08-01, while DeepSeek R1 Distill Llama 70B's cutoff date is not specified.

We can confirm Gemini 2.0 Flash Thinking's training data extends to 2024-08-01, but cannot make a direct comparison without DeepSeek R1 Distill Llama 70B's cutoff date.

DeepSeek R1 Distill Llama 70B

Gemini 2.0 Flash Thinking

Aug 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek R1 Distill Llama 70B and Gemini 2.0 Flash Thinking side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Llama 70B
✓ Preferred
Gemini 2.0 Flash Thinking
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs Gemini 2.0 Flash Thinking.

Which is better, DeepSeek R1 Distill Llama 70B or Gemini 2.0 Flash Thinking?

DeepSeek R1 Distill Llama 70B and Gemini 2.0 Flash Thinking are closely matched on the LLM Stats Score at 14.5 and 16.7. DeepSeek R1 Distill Llama 70B is made by DeepSeek and Gemini 2.0 Flash Thinking 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 R1 Distill Llama 70B compare to Gemini 2.0 Flash Thinking in benchmarks?

DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. Gemini 2.0 Flash Thinking scores MMMU: 75.4%, GPQA: 74.2%, AIME 2024: 73.3%.

What are the context window sizes for DeepSeek R1 Distill Llama 70B and Gemini 2.0 Flash Thinking?

DeepSeek R1 Distill Llama 70B supports 128K tokens and Gemini 2.0 Flash Thinking supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek R1 Distill Llama 70B and Gemini 2.0 Flash Thinking?

Key differences include LLM Stats Score (14.5 vs 16.7), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Distill Llama 70B and Gemini 2.0 Flash Thinking?

DeepSeek R1 Distill Llama 70B is developed by DeepSeek and Gemini 2.0 Flash Thinking is developed by Google.