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LFM3-VL-2B vs LongCat-Flash-Chat

LongCat-Flash-Chat leads the LLM Stats Score 19.2 to 15.5.

Liquid AI · Meituan · Updated for 2026

Which is better?

LongCat-Flash-Chat leads the overall LLM Stats Score 19.2 to 15.5, ranking #238 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-Chat

  • overall performance matters — it scores 19.2 and ranks #238 on LLM Stats

At a glance

The differences that matter most.

LFM3-VL-2B
Liquid AI
LongCat-Flash-Chat
Meituan
Core performance indexes
LLM Stats Score
15.5
#265
19.2
#238
Reasoning
16.2
#252
19.2
#233
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-Chat
Math
19.0#187
18.9#189
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

41 reported for LFM3-VL-2B · 16 for LongCat-Flash-Chat

No common benchmarks found

LFM3-VL-2B and LongCat-Flash-Chatdon'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-Chat has 558.1B more parameters than LFM3-VL-2B, making it 29066.7% larger.

Liquid AI
LFM3-VL-2B
1.9Bparameters
Meituan
LongCat-Flash-Chat
560.0Bparameters
1.9B
LFM3-VL-2B
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).

Liquid AI
LFM3-VL-2B
Input- tokens
Output- tokens
Meituan
LongCat-Flash-Chat
Input128,000 tokens
Output128,000 tokens
Fri Nov 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

LFM3-VL-2B supports multimodal inputs, whereas LongCat-Flash-Chat 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-Chat

Text
Images
Audio
Video

License

Usage and distribution terms

LFM3-VL-2B is licensed under LFM Open License v1.0, while LongCat-Flash-Chat 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-Chat

MIT

Open weights

Release Timeline

When each model was launched

LFM3-VL-2B was released on 2026-10-27, while LongCat-Flash-Chat was released on 2025-08-29.

LFM3-VL-2B is 14 months newer than LongCat-Flash-Chat.

LFM3-VL-2B

Oct 27, 2026

1 weeks ago

1.2yr newer
LongCat-Flash-Chat

Aug 29, 2025

1.2 years 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-Chat side-by-side, then vote on the output you prefer.

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

FAQ

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

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

LongCat-Flash-Chat leads the LLM Stats Score 19.2 to 15.5. LFM3-VL-2B is made by Liquid AI 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 LFM3-VL-2B compare to LongCat-Flash-Chat in benchmarks?

LFM3-VL-2B scores DocVQA: 96.7%, CountBench: 93.0%, ChartQA: 92.7%, RefCOCO-avg: 90.5%, POPE: 88.7%. 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 LFM3-VL-2B and LongCat-Flash-Chat?

LFM3-VL-2B 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 LFM3-VL-2B and LongCat-Flash-Chat?

Key differences include LLM Stats Score (15.5 vs 19.2), 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-Chat?

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

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