Model Comparison

DeepSeek R1 Zero vs LongCat-Flash-Thinking

LongCat-Flash-Thinking significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek R1 Zero outperforms in 0 benchmarks, while LongCat-Flash-Thinking is better at 4 benchmarks (AIME 2024, GPQA, LiveCodeBench, MATH-500).

LongCat-Flash-Thinking significantly outperforms across most benchmarks.

Sat Apr 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 18 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Zero
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Meituan
LongCat-Flash-Thinking
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

111.0B diff

DeepSeek R1 Zero has 111.0B more parameters than LongCat-Flash-Thinking, making it 19.8% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Meituan
LongCat-Flash-Thinking
560.0Bparameters
671.0B
DeepSeek R1 Zero
560.0B
LongCat-Flash-Thinking

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Thinking specifies input context (128,000 tokens). Only LongCat-Flash-Thinking specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Sat Apr 18 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

LongCat-Flash-Thinking

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while LongCat-Flash-Thinking was released on 2025-09-22.

LongCat-Flash-Thinking is 8 months newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.2 years ago

LongCat-Flash-Thinking

Sep 22, 2025

6 months ago

8mo 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
Meituan
Larger context window (128,000 tokens)
Higher AIME 2024 score (93.3% vs 86.7%)
Higher GPQA score (81.5% vs 73.3%)
Higher LiveCodeBench score (79.4% vs 50.0%)
Higher MATH-500 score (99.2% vs 95.9%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Zero
Meituan
LongCat-Flash-Thinking

FAQ

Common questions about DeepSeek R1 Zero vs LongCat-Flash-Thinking

LongCat-Flash-Thinking significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and LongCat-Flash-Thinking is made by Meituan. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%.
DeepSeek R1 Zero supports an unknown number of tokens and LongCat-Flash-Thinking supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
DeepSeek R1 Zero is developed by DeepSeek and LongCat-Flash-Thinking is developed by Meituan.