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DeepSeek R1 Zero vs Mistral Large 2

DeepSeek R1 Zero leads the LLM Stats Score 16.0 to 7.4.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek R1 Zero leads the overall LLM Stats Score 16.0 to 7.4, ranking #234 overall.

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

Choose DeepSeek R1 Zero

  • overall performance matters — it scores 16.0 and ranks #234 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Jan 2025

Choose Mistral Large 2

  • you want predictable pricing at $2.00/M input and $6.00/M output

At a glance

The differences that matter most.

DeepSeek R1 Zero
DeepSeek
Mistral Large 2
Mistral AI
Core performance indexes
LLM Stats Score
16.0
#234
7.4
#296
Reasoning
16.3
#224
7.3
#289
Coding
4.3
#217
13.0
#146
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$2.00 / M
Output price
— / M
$6.00 / M
Context window
—
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Zero
Mistral Large 2
Math
17.5#196
11.3#246
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Zero · 5 for Mistral Large 2

No common benchmarks found

DeepSeek R1 Zero and Mistral Large 2don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

548.0B diff

DeepSeek R1 Zero has 548.0B more parameters than Mistral Large 2, making it 445.5% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Mistral AI
Mistral Large 2
123.0Bparameters
671.0B
DeepSeek R1 Zero
123.0B
Mistral Large 2

Context Window

Maximum input and output token capacity

Only Mistral Large 2 specifies input context (128,000 tokens). Only Mistral Large 2 specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Mistral AI
Mistral Large 2
Input128,000 tokens
Output128,000 tokens
Tue Sep 29 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Mistral Large 2 uses Mistral Research License.

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

DeepSeek R1 Zero

MIT

Open weights

Mistral Large 2

Mistral Research License

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Mistral Large 2 was released on 2024-07-24.

DeepSeek R1 Zero is 6 months newer than Mistral Large 2.

DeepSeek R1 Zero

Jan 20, 2025

1.7 years ago

6mo newer
Mistral Large 2

Jul 24, 2024

2.2 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek R1 Zero and Mistral Large 2 side-by-side, then vote on the output you prefer.

DeepSeek R1 Zero
✓ Preferred
Mistral Large 2
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs Mistral Large 2.

Which is better, DeepSeek R1 Zero or Mistral Large 2?

DeepSeek R1 Zero leads the LLM Stats Score 16.0 to 7.4. DeepSeek R1 Zero is made by DeepSeek and Mistral Large 2 is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek R1 Zero compare to Mistral Large 2 in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Mistral Large 2 scores GSM8k: 93.0%, HumanEval: 92.0%, MT-Bench: 86.3%, MMLU: 84.0%, MMLU French: 82.8%.

What are the context window sizes for DeepSeek R1 Zero and Mistral Large 2?

DeepSeek R1 Zero supports an unknown number of tokens and Mistral Large 2 supports 128K 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 Zero and Mistral Large 2?

Key differences include LLM Stats Score (16.0 vs 7.4), licensing (MIT vs Mistral Research License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Mistral Large 2?

DeepSeek R1 Zero is developed by DeepSeek and Mistral Large 2 is developed by Mistral AI.

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