Model Comparison

DeepSeek R1 Zero vs MiniMax M1 80K

Both models are evenly matched across the benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek R1 Zero outperforms in 2 benchmarks (AIME 2024, GPQA), while MiniMax M1 80K is better at 2 benchmarks (LiveCodeBench, MATH-500).

Both models are evenly matched across the benchmarks.

Sat May 23 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

215.0B diff

DeepSeek R1 Zero has 215.0B more parameters than MiniMax M1 80K, making it 47.1% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
MiniMax
MiniMax M1 80K
456.0Bparameters
671.0B
DeepSeek R1 Zero
456.0B
MiniMax M1 80K

Context Window

Maximum input and output token capacity

Only MiniMax M1 80K specifies input context (1,000,000 tokens). Only MiniMax M1 80K specifies output context (40,000 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
MiniMax
MiniMax M1 80K
Input1,000,000 tokens
Output40,000 tokens
Sat May 23 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek R1 Zero

MIT

Open weights

MiniMax M1 80K

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while MiniMax M1 80K was released on 2025-06-16.

MiniMax M1 80K is 5 months newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.3 years ago

MiniMax M1 80K

Jun 16, 2025

11 months ago

4mo newer

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→

Key Takeaways

DeepSeek
Higher AIME 2024 score (86.7% vs 86.0%)
Higher GPQA score (73.3% vs 70.0%)
MiniMax
Larger context window (1,000,000 tokens)
Higher LiveCodeBench score (65.0% vs 50.0%)
Higher MATH-500 score (96.8% vs 95.9%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Zero
MiniMax
MiniMax M1 80K

FAQ

Common questions about DeepSeek R1 Zero vs MiniMax M1 80K.

Which is better, DeepSeek R1 Zero or MiniMax M1 80K?

Both models are evenly matched across the benchmarks. DeepSeek R1 Zero is made by DeepSeek and MiniMax M1 80K is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Zero compare to MiniMax M1 80K in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. MiniMax M1 80K scores MATH-500: 96.8%, ZebraLogic: 86.8%, AIME 2024: 86.0%, MMLU-Pro: 81.1%, AIME 2025: 76.9%.

What are the context window sizes for DeepSeek R1 Zero and MiniMax M1 80K?

DeepSeek R1 Zero supports an unknown number of tokens and MiniMax M1 80K supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Who makes DeepSeek R1 Zero and MiniMax M1 80K?

DeepSeek R1 Zero is developed by DeepSeek and MiniMax M1 80K is developed by MiniMax.