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DeepSeek R1 Zero vs Pixtral Large

DeepSeek R1 Zero and Pixtral Large are closely matched at 16.2 and 12.2 on the LLM Stats Score.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek R1 Zero and Pixtral Large are closely matched on the overall LLM Stats Score at 16.2 and 12.2.

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

Choose DeepSeek R1 Zero

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

Choose Pixtral Large

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

At a glance

The differences that matter most.

Core performance indexes
16.2
#205
12.2
#235
16.5
#197
13.4
#220
Cost, coverage & limits
Benchmark wins
Input price
— / M
$2.00 / M
Output price
— / M
$6.00 / M
Context window
128,000

Individual benchmarks

4 reported for DeepSeek R1 Zero · 7 for Pixtral Large

No common benchmarks found

DeepSeek R1 Zero and Pixtral Largedon'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

547.0B diff

DeepSeek R1 Zero has 547.0B more parameters than Pixtral Large, making it 441.1% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Mistral AI
Pixtral Large
124.0Bparameters
671.0B
DeepSeek R1 Zero
124.0B
Pixtral Large

Context Window

Maximum input and output token capacity

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

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Mistral AI
Pixtral Large
Input128,000 tokens
Output128,000 tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Pixtral Large supports multimodal inputs, whereas DeepSeek R1 Zero does not.

Pixtral Large can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Zero

Text
Images
Audio
Video

Pixtral Large

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.

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

DeepSeek R1 Zero

MIT

Open weights

Pixtral Large

Mistral Research License (MRL) for research; Mistral Commercial License for commercial use

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Pixtral Large was released on 2024-11-18.

DeepSeek R1 Zero is 2 months newer than Pixtral Large.

DeepSeek R1 Zero

Jan 20, 2025

1.6 years ago

2mo newer
Pixtral Large

Nov 18, 2024

1.8 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?Start an Issue discussion

Judge for yourself.

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

DeepSeek R1 Zero
✓ Preferred
Pixtral Large
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs Pixtral Large.

Which is better, DeepSeek R1 Zero or Pixtral Large?

DeepSeek R1 Zero and Pixtral Large are closely matched on the LLM Stats Score at 16.2 and 12.2. DeepSeek R1 Zero is made by DeepSeek and Pixtral Large 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 Pixtral Large in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Pixtral Large scores AI2D: 93.8%, DocVQA: 93.3%, ChartQA: 88.1%, VQAv2: 80.9%, MM-MT-Bench: 74.0%.

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

DeepSeek R1 Zero supports an unknown number of tokens and Pixtral Large 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 Pixtral Large?

Key differences include LLM Stats Score (16.2 vs 12.2), multimodal support (no vs yes), licensing (MIT vs Mistral Research License (MRL) for research; Mistral Commercial License for commercial use). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Pixtral Large?

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