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DeepSeek R1 Zero vs LongCat-Flash-Chat

DeepSeek R1 Zero and LongCat-Flash-Chat are closely matched at 16.0 and 19.8 on the LLM Stats Score.

DeepSeek · Meituan · Updated for 2026

Which is better?

DeepSeek R1 Zero and LongCat-Flash-Chat are closely matched on the overall LLM Stats Score at 16.0 and 19.8.

In the 3 individual benchmarks reported for both models, DeepSeek R1 Zero wins 2; this is a narrower head-to-head signal than the composite indexes.

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

Choose DeepSeek R1 Zero

  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results

Choose LongCat-Flash-Chat

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

At a glance

The differences that matter most.

Core performance indexes
16.0
#242
19.8
#214
16.3
#232
19.7
#210
4.2
#223
12.3
#161
Cost, coverage & limits
Benchmark wins
2 of 3
1 of 3
Input price
— / M
$0.30 / M
Output price
— / M
$1.20 / M
Context window
—
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Zero
LongCat-Flash-Chat
17.5#200
18.9#180
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Zero · 16 for LongCat-Flash-Chat

3 shared

DeepSeek R1 Zero outperforms in 2 benchmarks (GPQA, LiveCodeBench), while LongCat-Flash-Chat is better at 1 benchmark (MATH-500).

DeepSeek R1 Zero shows notably better performance in the majority of benchmarks.

Fri Oct 09 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

111.0B diff

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

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

Context Window

Maximum input and output token capacity

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

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Chat
Input128,000 tokens
Output128,000 tokens
Fri Oct 09 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-Chat

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while LongCat-Flash-Chat was released on 2025-08-29.

LongCat-Flash-Chat is 7 months newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.7 years ago

LongCat-Flash-Chat

Aug 29, 2025

1.1 years ago

7mo 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?

Judge for yourself.

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

DeepSeek R1 Zero
✓ Preferred
LongCat-Flash-Chat
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs LongCat-Flash-Chat.

Which is better, DeepSeek R1 Zero or LongCat-Flash-Chat?

DeepSeek R1 Zero and LongCat-Flash-Chat are closely matched on the LLM Stats Score at 16.0 and 19.8. DeepSeek R1 Zero is made by DeepSeek and LongCat-Flash-Chat is made by Meituan. 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 LongCat-Flash-Chat in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. LongCat-Flash-Chat scores MATH-500: 96.4%, MMLU: 89.7%, IFEval: 89.6%, ZebraLogic: 89.3%, HumanEval: 88.4%.

What are the context window sizes for DeepSeek R1 Zero and LongCat-Flash-Chat?

DeepSeek R1 Zero supports an unknown number of tokens and LongCat-Flash-Chat 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 LongCat-Flash-Chat?

Key differences include LLM Stats Score (16.0 vs 19.8). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and LongCat-Flash-Chat?

DeepSeek R1 Zero is developed by DeepSeek and LongCat-Flash-Chat is developed by Meituan.