Model Comparison

DeepSeek R1 Zero vs Mistral NeMo Instruct

Comparing DeepSeek R1 Zero and Mistral NeMo Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

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

Arena Performance

Human preference votes

Model Size

Parameter count comparison

659.0B diff

DeepSeek R1 Zero has 659.0B more parameters than Mistral NeMo Instruct, making it 5491.7% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Mistral AI
Mistral NeMo Instruct
12.0Bparameters
671.0B
DeepSeek R1 Zero
12.0B
Mistral NeMo Instruct

Context Window

Maximum input and output token capacity

Only Mistral NeMo Instruct specifies input context (128,000 tokens). Only Mistral NeMo Instruct specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Sat May 23 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Mistral NeMo Instruct 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

Mistral NeMo Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Mistral NeMo Instruct was released on 2024-07-18.

DeepSeek R1 Zero is 6 months newer than Mistral NeMo Instruct.

DeepSeek R1 Zero

Jan 20, 2025

1.3 years ago

6mo newer
Mistral NeMo Instruct

Jul 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

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Key Takeaways

DeepSeek

No standout differentiators in the data we have for this pair.

Mistral AI
Larger context window (128,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Zero
Mistral AI
Mistral NeMo Instruct

FAQ

Common questions about DeepSeek R1 Zero vs Mistral NeMo Instruct.

Which is better, DeepSeek R1 Zero or Mistral NeMo Instruct?

DeepSeek R1 Zero (DeepSeek) and Mistral NeMo Instruct (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek R1 Zero compare to Mistral NeMo Instruct in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%.

What are the context window sizes for DeepSeek R1 Zero and Mistral NeMo Instruct?

DeepSeek R1 Zero supports an unknown number of tokens and Mistral NeMo Instruct 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 NeMo Instruct?

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Mistral NeMo Instruct?

DeepSeek R1 Zero is developed by DeepSeek and Mistral NeMo Instruct is developed by Mistral AI.