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DeepSeek R1 Zero vs Pixtral-12B

DeepSeek R1 Zero leads the LLM Stats Score 16.2 to -1.4.

DeepSeek · Mistral AI · Updated for 2026

Which is better?

DeepSeek R1 Zero leads the overall LLM Stats Score 16.2 to -1.4, ranking #212 overall.

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

Choose DeepSeek R1 Zero

  • overall performance matters — it scores 16.2 and ranks #212 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Jan 2025

Choose Pixtral-12B

  • you want predictable pricing at $0.15/M input and $0.15/M output

At a glance

The differences that matter most.

Core performance indexes
16.2
#212
-1.4
#323
16.5
#203
-3.4
#323
4.4
#200
-2.5
#240
Cost, coverage & limits
Benchmark wins
Input price
— / M
$0.15 / M
Output price
— / M
$0.15 / M
Context window
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Zero
Pixtral-12B
17.7#186
1.3#285
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Zero · 12 for Pixtral-12B

No common benchmarks found

DeepSeek R1 Zero and Pixtral-12Bdon'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

658.6B diff

DeepSeek R1 Zero has 658.6B more parameters than Pixtral-12B, making it 5311.3% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Mistral AI
Pixtral-12B
12.4Bparameters
671.0B
DeepSeek R1 Zero
12.4B
Pixtral-12B

Context Window

Maximum input and output token capacity

Only Pixtral-12B specifies input context (128,000 tokens). Only Pixtral-12B specifies output context (8,192 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Mistral AI
Pixtral-12B
Input128,000 tokens
Output8,192 tokens
Thu Sep 03 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Pixtral-12B supports multimodal inputs, whereas DeepSeek R1 Zero does not.

Pixtral-12B 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-12B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Pixtral-12B uses Apache 2.0.

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

DeepSeek R1 Zero

MIT

Open weights

Pixtral-12B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Pixtral-12B was released on 2024-09-17.

DeepSeek R1 Zero is 4 months newer than Pixtral-12B.

DeepSeek R1 Zero

Jan 20, 2025

1.6 years ago

4mo newer
Pixtral-12B

Sep 17, 2024

2.0 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-12B side-by-side, then vote on the output you prefer.

DeepSeek R1 Zero
✓ Preferred
Pixtral-12B
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs Pixtral-12B.

Which is better, DeepSeek R1 Zero or Pixtral-12B?

DeepSeek R1 Zero leads the LLM Stats Score 16.2 to -1.4. DeepSeek R1 Zero is made by DeepSeek and Pixtral-12B 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-12B in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Pixtral-12B scores DocVQA: 90.7%, ChartQA: 81.8%, VQAv2: 78.6%, MT-Bench: 76.8%, HumanEval: 72.0%.

What are the context window sizes for DeepSeek R1 Zero and Pixtral-12B?

DeepSeek R1 Zero supports an unknown number of tokens and Pixtral-12B 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-12B?

Key differences include LLM Stats Score (16.2 vs -1.4), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Pixtral-12B?

DeepSeek R1 Zero is developed by DeepSeek and Pixtral-12B is developed by Mistral AI.