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LFM3-VL-2B vs Qwen3 VL 30B A3B Thinking

LFM3-VL-2B and Qwen3 VL 30B A3B Thinking are closely matched at 15.5 and 17.7 on the LLM Stats Score.

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

Which is better?

LFM3-VL-2B and Qwen3 VL 30B A3B Thinking are closely matched on the overall LLM Stats Score at 15.5 and 17.7.

In the 20 individual benchmarks reported for both models, Qwen3 VL 30B A3B Thinking 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

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

Choose Qwen3 VL 30B A3B Thinking

  • you value its reported benchmark strengths — it wins 12 of 20 exact shared results

At a glance

The differences that matter most.

LFM3-VL-2B
Liquid AI
Qwen3 VL 30B A3B Thinking
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
15.5
#265
17.7
#251
Reasoning
16.2
#252
18.9
#237
Cost, coverage & limits
Benchmark wins
8 of 20
12 of 20
Input price
— / M
$0.20 / M
Output price
— / M
$0.99 / M
Context window
—
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
LFM3-VL-2B
Qwen3 VL 30B A3B Thinking
Math
19.0#187
22.1#153
Vision
11.4#133
12.1#127
Multimodal
12.6#124
14.7#112
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

41 reported for LFM3-VL-2B · 50 for Qwen3 VL 30B A3B Thinking

20 shared

LFM3-VL-2B outperforms in 8 benchmarks (BLINK, CharXiv-D, CharXiv-R, ERQA, MathVista-Mini, OCRBench, OCRBench-V2 (en), RealWorldQA), while Qwen3 VL 30B A3B Thinking is better at 12 benchmarks (Hallusion Bench, LVBench, MathVision, MLVU-M, MMBench-V1.1, MMMU-Pro, MMMU (val), MMStar, MuirBench, MVBench, ScreenSpot Pro, VideoMMMU).

Qwen3 VL 30B A3B Thinking has a slight edge in benchmark performance.

Fri Nov 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

29.1B diff

Qwen3 VL 30B A3B Thinking has 29.1B more parameters than LFM3-VL-2B, making it 1514.6% larger.

Liquid AI
LFM3-VL-2B
1.9Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
1.9B
LFM3-VL-2B
31.0B
Qwen3 VL 30B A3B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 30B A3B Thinking specifies input context (131,072 tokens). Only Qwen3 VL 30B A3B Thinking specifies output context (32,768 tokens).

Liquid AI
LFM3-VL-2B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Fri Nov 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both LFM3-VL-2B and Qwen3 VL 30B A3B 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 30B A3B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

LFM3-VL-2B is licensed under LFM Open License v1.0, while Qwen3 VL 30B A3B 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 30B A3B 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 30B A3B Thinking was released on 2025-09-22.

LFM3-VL-2B is 13 months newer than Qwen3 VL 30B A3B Thinking.

LFM3-VL-2B

Oct 27, 2026

1 weeks ago

1.1yr newer
Qwen3 VL 30B A3B 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 30B A3B Thinking side-by-side, then vote on the output you prefer.

LFM3-VL-2B
✓ Preferred
Qwen3 VL 30B A3B Thinking
Open in Playground

FAQ

Common questions about LFM3-VL-2B vs Qwen3 VL 30B A3B Thinking.

Which is better, LFM3-VL-2B or Qwen3 VL 30B A3B Thinking?

LFM3-VL-2B and Qwen3 VL 30B A3B Thinking are closely matched on the LLM Stats Score at 15.5 and 17.7. LFM3-VL-2B is made by Liquid AI and Qwen3 VL 30B A3B 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 30B A3B 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 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%.

What are the context window sizes for LFM3-VL-2B and Qwen3 VL 30B A3B Thinking?

LFM3-VL-2B supports an unknown number of tokens and Qwen3 VL 30B A3B Thinking supports 131K 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 30B A3B Thinking?

Key differences include LLM Stats Score (15.5 vs 17.7), 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 30B A3B Thinking?

LFM3-VL-2B is developed by Liquid AI and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.

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