The AI arena is free today

Open Superagent

LFM3-VL-2B vs Qwen3 VL 4B Thinking

LFM3-VL-2B leads the LLM Stats Score 15.5 to 12.4.

Liquid AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

LFM3-VL-2B leads the overall LLM Stats Score 15.5 to 12.4, ranking #265 overall.

In the 20 individual benchmarks reported for both models, LFM3-VL-2B wins 12; 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 LFM3-VL-2B

  • overall performance matters — it scores 15.5 and ranks #265 on LLM Stats
  • you value its reported benchmark strengths — it wins 12 of 20 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose Qwen3 VL 4B Thinking

  • you want predictable pricing at $0.10/M input and $1.00/M output

At a glance

The differences that matter most.

LFM3-VL-2B
Liquid AI
Qwen3 VL 4B Thinking
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
15.5
#265
12.4
#289
Reasoning
16.2
#252
13.5
#270
Cost, coverage & limits
Benchmark wins
12 of 20
8 of 20
Input price
— / M
$0.10 / M
Output price
— / M
$1.00 / M
Context window
—
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
LFM3-VL-2B
Qwen3 VL 4B Thinking
Math
19.0#187
15.4#234
Vision
11.4#133
7.6#167
Multimodal
12.6#124
10.4#137
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

41 reported for LFM3-VL-2B · 48 for Qwen3 VL 4B Thinking

20 shared

LFM3-VL-2B outperforms in 12 benchmarks (BLINK, CharXiv-D, CharXiv-R, ERQA, Hallusion Bench, MathVista-Mini, MMStar, MVBench, OCRBench, OCRBench-V2 (en), RealWorldQA, ScreenSpot Pro), while Qwen3 VL 4B Thinking is better at 8 benchmarks (LVBench, MathVision, MLVU-M, MMBench-V1.1, MMMU-Pro, MMMU (val), MuirBench, VideoMMMU).

LFM3-VL-2B has a slight edge in benchmark performance.

Wed Nov 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

2.1B diff

Qwen3 VL 4B Thinking has 2.1B more parameters than LFM3-VL-2B, making it 108.3% larger.

Liquid AI
LFM3-VL-2B
1.9Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
1.9B
LFM3-VL-2B
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 4B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 4B Thinking specifies output context (262,144 tokens).

Liquid AI
LFM3-VL-2B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Wed Nov 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both LFM3-VL-2B and Qwen3 VL 4B Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

LFM3-VL-2B

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

LFM3-VL-2B is licensed under LFM Open License v1.0, while Qwen3 VL 4B Thinking uses Apache 2.0.

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

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

LFM3-VL-2B was released on 2026-10-27, while Qwen3 VL 4B Thinking was released on 2025-09-22.

LFM3-VL-2B is 13 months newer than Qwen3 VL 4B Thinking.

LFM3-VL-2B

Oct 27, 2026

1 weeks ago

1.1yr newer
Qwen3 VL 4B Thinking

Sep 22, 2025

1.1 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 Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.

LFM3-VL-2B
✓ Preferred
Qwen3 VL 4B Thinking
Open in Playground

FAQ

Common questions about LFM3-VL-2B vs Qwen3 VL 4B Thinking.

Which is better, LFM3-VL-2B or Qwen3 VL 4B Thinking?

LFM3-VL-2B leads the LLM Stats Score 15.5 to 12.4. LFM3-VL-2B is made by Liquid AI and Qwen3 VL 4B Thinking is made by Alibaba Cloud / Qwen Team. 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 Qwen3 VL 4B Thinking in benchmarks?

LFM3-VL-2B scores DocVQA: 96.7%, CountBench: 93.0%, ChartQA: 92.7%, RefCOCO-avg: 90.5%, POPE: 88.7%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

What are the context window sizes for LFM3-VL-2B and Qwen3 VL 4B Thinking?

LFM3-VL-2B supports an unknown number of tokens and Qwen3 VL 4B Thinking supports 262K 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 Qwen3 VL 4B Thinking?

Key differences include LLM Stats Score (15.5 vs 12.4), licensing (LFM Open License v1.0 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes LFM3-VL-2B and Qwen3 VL 4B Thinking?

LFM3-VL-2B is developed by Liquid AI and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.

Related comparisons