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LongCat-2.5 vs LongCat-Flash-Thinking-2601

LongCat-2.5 leads the LLM Stats Score 50.0 to 34.7. LongCat-2.5 and LongCat-Flash-Thinking-2601 cost the same.

Meituan · Meituan · Updated for 2026

Which is better?

LongCat-2.5 leads the overall LLM Stats Score 50.0 to 34.7, ranking #20 overall.

In the 1 individual benchmarks reported for both models, LongCat-2.5 wins 1; this is a narrower head-to-head signal than the composite indexes.

LongCat-2.5 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose LongCat-2.5

  • overall performance matters — it scores 50.0 and ranks #20 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Nov 2026

Choose LongCat-Flash-Thinking-2601

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

LongCat-2.5
Meituan
LongCat-Flash-Thinking-2601
Meituan
Core performance indexes
LLM Stats Score
50.0
#20
34.7
#115
Reasoning
48.3
#21
34.8
#108
Coding
38.6
#27
18.9
#135
Agents
36.3
#23
8.3
#162
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.30 / M
$0.30 / M
Output price
$1.20 / M
$1.20 / M
Context window
1,048,576
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
LongCat-2.5
LongCat-Flash-Thinking-2601
Math
37.2#37
30.3#84
Tool use
30.2#15
23.4#50
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for LongCat-2.5 · 11 for LongCat-Flash-Thinking-2601

1 shared

LongCat-2.5 outperforms in 1 benchmarks (BrowseComp), while LongCat-Flash-Thinking-2601 is better at 0 benchmarks.

LongCat-2.5 significantly outperforms across most benchmarks.

Wed Nov 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

For input processing, LongCat-2.5 ($0.30/1M tokens) costs the same as LongCat-Flash-Thinking-2601 ($0.30/1M tokens).

For output processing, LongCat-2.5 ($1.20/1M tokens) costs the same as LongCat-Flash-Thinking-2601 ($1.20/1M tokens).

In conclusion, LongCat-2.5 and LongCat-Flash-Thinking-2601 cost the same.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Nov 04 2026 • llm-stats.com
Meituan
LongCat-2.5
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Meituan
LongCat-Flash-Thinking-2601
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Notice missing or incorrect data?

Model Size

Parameter count comparison

1040.0B diff

LongCat-2.5 has 1040.0B more parameters than LongCat-Flash-Thinking-2601, making it 185.7% larger.

Meituan
LongCat-2.5
1.6Tparameters
Meituan
LongCat-Flash-Thinking-2601
560.0Bparameters
1600.0B
LongCat-2.5
560.0B
LongCat-Flash-Thinking-2601

Context Window

Maximum input and output token capacity

LongCat-2.5 accepts 1,048,576 input tokens compared to LongCat-Flash-Thinking-2601's 128,000 tokens. LongCat-2.5 can generate longer responses up to 131,072 tokens, while LongCat-Flash-Thinking-2601 is limited to 128,000 tokens.

Meituan
LongCat-2.5
Input1,048,576 tokens
Output131,072 tokens
Meituan
LongCat-Flash-Thinking-2601
Input128,000 tokens
Output128,000 tokens
Wed Nov 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

LongCat-2.5 supports multimodal inputs, whereas LongCat-Flash-Thinking-2601 does not.

LongCat-2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-2.5

Text
Images
Audio
Video

LongCat-Flash-Thinking-2601

Text
Images
Audio
Video

Release Timeline

When each model was launched

LongCat-2.5 was released on 2026-11-01, while LongCat-Flash-Thinking-2601 was released on 2026-01-14.

LongCat-2.5 is 10 months newer than LongCat-Flash-Thinking-2601.

LongCat-2.5

Nov 1, 2026

3 days ago

9mo newer
LongCat-Flash-Thinking-2601

Jan 14, 2026

9 months 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

Provider Availability

LongCat-2.5 is available from Meituan. LongCat-Flash-Thinking-2601 is available from Meituan.

LongCat-2.5

meituan logo
Meituan
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

LongCat-Flash-Thinking-2601

meituan logo
Meituan
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against LongCat-2.5 and LongCat-Flash-Thinking-2601 side-by-side, then vote on the output you prefer.

LongCat-2.5
✓ Preferred
LongCat-Flash-Thinking-2601
Open in Playground

FAQ

Common questions about LongCat-2.5 vs LongCat-Flash-Thinking-2601.

Which is better, LongCat-2.5 or LongCat-Flash-Thinking-2601?

LongCat-2.5 leads the LLM Stats Score 50.0 to 34.7. LongCat-2.5 is made by Meituan and LongCat-Flash-Thinking-2601 is made by Meituan. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does LongCat-2.5 compare to LongCat-Flash-Thinking-2601 in benchmarks?

LongCat-2.5 scores MathVision: 96.5%, BrowseComp: 91.9%, CharXiv-R: 90.2%, Terminal-Bench 2.1: 88.4%, Video-MME: 85.2%. LongCat-Flash-Thinking-2601 scores AIME 2025: 99.6%, Tau2 Telecom: 99.3%, Tau2 Retail: 88.6%, LiveCodeBench: 82.8%, GPQA: 80.5%.

Is LongCat-2.5 cheaper than LongCat-Flash-Thinking-2601?

Both models cost $0.30 per million input tokens.

What are the context window sizes for LongCat-2.5 and LongCat-Flash-Thinking-2601?

LongCat-2.5 supports 1.0M tokens and LongCat-Flash-Thinking-2601 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 LongCat-2.5 and LongCat-Flash-Thinking-2601?

Key differences include LLM Stats Score (50.0 vs 34.7), context window (1.0M vs 128K), multimodal support (yes vs no), licensing (Unknown vs MIT). See the full comparison above for benchmark-by-benchmark results.

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