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LFM3-VL-2B vs LongCat-Flash-Thinking-2601

LongCat-Flash-Thinking-2601 leads the LLM Stats Score 34.7 to 15.5.

Liquid AI · Meituan · Updated for 2026

Which is better?

LongCat-Flash-Thinking-2601 leads the overall LLM Stats Score 34.7 to 15.5, ranking #116 overall.

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

Choose LFM3-VL-2B

  • you want the most recent training data — it shipped Oct 2026

Choose LongCat-Flash-Thinking-2601

  • overall performance matters — it scores 34.7 and ranks #116 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes

At a glance

The differences that matter most.

LFM3-VL-2B
Liquid AI
LongCat-Flash-Thinking-2601
Meituan
Core performance indexes
LLM Stats Score
15.5
#265
34.7
#116
Reasoning
16.2
#252
34.8
#108
Cost, coverage & limits
Benchmark wins
—
—
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
LFM3-VL-2B
LongCat-Flash-Thinking-2601
Math
19.0#187
30.3#84
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

41 reported for LFM3-VL-2B · 11 for LongCat-Flash-Thinking-2601

No common benchmarks found

LFM3-VL-2B and LongCat-Flash-Thinking-2601don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

558.1B diff

LongCat-Flash-Thinking-2601 has 558.1B more parameters than LFM3-VL-2B, making it 29066.7% larger.

Liquid AI
LFM3-VL-2B
1.9Bparameters
Meituan
LongCat-Flash-Thinking-2601
560.0Bparameters
1.9B
LFM3-VL-2B
560.0B
LongCat-Flash-Thinking-2601

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Thinking-2601 specifies input context (128,000 tokens). Only LongCat-Flash-Thinking-2601 specifies output context (128,000 tokens).

Liquid AI
LFM3-VL-2B
Input- tokens
Output- 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

LFM3-VL-2B supports multimodal inputs, whereas LongCat-Flash-Thinking-2601 does not.

LFM3-VL-2B can handle both text and other forms of data like images, making it suitable for multimodal applications.

LFM3-VL-2B

Text
Images
Audio
Video

LongCat-Flash-Thinking-2601

Text
Images
Audio
Video

License

Usage and distribution terms

LFM3-VL-2B is licensed under LFM Open License v1.0, while LongCat-Flash-Thinking-2601 uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

LFM3-VL-2B

LFM Open License v1.0

Open weights

LongCat-Flash-Thinking-2601

MIT

Open weights

Release Timeline

When each model was launched

LFM3-VL-2B was released on 2026-10-27, while LongCat-Flash-Thinking-2601 was released on 2026-01-14.

LFM3-VL-2B is 10 months newer than LongCat-Flash-Thinking-2601.

LFM3-VL-2B

Oct 27, 2026

1 weeks 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

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against LFM3-VL-2B and LongCat-Flash-Thinking-2601 side-by-side, then vote on the output you prefer.

LFM3-VL-2B
✓ Preferred
LongCat-Flash-Thinking-2601
Open in Playground

FAQ

Common questions about LFM3-VL-2B vs LongCat-Flash-Thinking-2601.

Which is better, LFM3-VL-2B or LongCat-Flash-Thinking-2601?

LongCat-Flash-Thinking-2601 leads the LLM Stats Score 34.7 to 15.5. LFM3-VL-2B is made by Liquid AI 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 LFM3-VL-2B compare to LongCat-Flash-Thinking-2601 in benchmarks?

LFM3-VL-2B scores DocVQA: 96.7%, CountBench: 93.0%, ChartQA: 92.7%, RefCOCO-avg: 90.5%, POPE: 88.7%. LongCat-Flash-Thinking-2601 scores AIME 2025: 99.6%, Tau2 Telecom: 99.3%, Tau2 Retail: 88.6%, LiveCodeBench: 82.8%, GPQA: 80.5%.

What are the context window sizes for LFM3-VL-2B and LongCat-Flash-Thinking-2601?

LFM3-VL-2B supports an unknown number of 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 LFM3-VL-2B and LongCat-Flash-Thinking-2601?

Key differences include LLM Stats Score (15.5 vs 34.7), multimodal support (yes vs no), licensing (LFM Open License v1.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes LFM3-VL-2B and LongCat-Flash-Thinking-2601?

LFM3-VL-2B is developed by Liquid AI and LongCat-Flash-Thinking-2601 is developed by Meituan.

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