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LFM2.5-VL-3B vs Qwen3 VL 30B A3B Thinking

Qwen3 VL 30B A3B Thinking leads the LLM Stats Score 17.8 to 2.7.

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

Which is better?

Qwen3 VL 30B A3B Thinking leads the overall LLM Stats Score 17.8 to 2.7, ranking #239 overall.

In the 13 individual benchmarks reported for both models, Qwen3 VL 30B A3B Thinking wins 11; 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 LFM2.5-VL-3B

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

Choose Qwen3 VL 30B A3B Thinking

  • overall performance matters — it scores 17.8 and ranks #239 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 11 of 13 exact shared results

At a glance

The differences that matter most.

LFM2.5-VL-3B
Liquid AI
Qwen3 VL 30B A3B Thinking
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
2.7
#335
17.8
#239
Reasoning
-2.7
#356
19.1
#225
Agents
-5.2
#208
7.0
#160
Cost, coverage & limits
Benchmark wins
2 of 13
11 of 13
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

2 shared
Index
LFM2.5-VL-3B
Qwen3 VL 30B A3B Thinking
Vision
1.1#196
12.1#123
Multimodal
2.9#162
14.8#109
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for LFM2.5-VL-3B · 50 for Qwen3 VL 30B A3B Thinking

13 shared

LFM2.5-VL-3B outperforms in 2 benchmarks (IFEval, OCRBench), while Qwen3 VL 30B A3B Thinking is better at 11 benchmarks (BLINK, Hallusion Bench, MathVista-Mini, MMBench-V1.1, MMMU-Pro, MMMU (val), MMStar, MuirBench, Multi-IF, OCRBench-V2 (en), RealWorldQA).

Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks.

Fri Oct 23 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

27.9B diff

Qwen3 VL 30B A3B Thinking has 27.9B more parameters than LFM2.5-VL-3B, making it 892.5% larger.

Liquid AI
LFM2.5-VL-3B
3.1Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
3.1B
LFM2.5-VL-3B
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
LFM2.5-VL-3B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Fri Oct 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both LFM2.5-VL-3B and Qwen3 VL 30B A3B Thinking support multimodal inputs.

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

LFM2.5-VL-3B

Text
Images
Audio
Video

Qwen3 VL 30B A3B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

LFM2.5-VL-3B 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.

LFM2.5-VL-3B

LFM Open License v1.0

Open weights

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

LFM2.5-VL-3B was released on 2026-08-12, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.

LFM2.5-VL-3B is 11 months newer than Qwen3 VL 30B A3B Thinking.

LFM2.5-VL-3B

Aug 12, 2026

2 months ago

10mo 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 LFM2.5-VL-3B and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.

LFM2.5-VL-3B
✓ Preferred
Qwen3 VL 30B A3B Thinking
Open in Playground

FAQ

Common questions about LFM2.5-VL-3B vs Qwen3 VL 30B A3B Thinking.

Which is better, LFM2.5-VL-3B or Qwen3 VL 30B A3B Thinking?

Qwen3 VL 30B A3B Thinking leads the LLM Stats Score 17.8 to 2.7. LFM2.5-VL-3B 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 LFM2.5-VL-3B compare to Qwen3 VL 30B A3B Thinking in benchmarks?

LFM2.5-VL-3B scores DocVQA: 91.1%, POPE: 88.7%, RefCOCO-avg: 87.9%, TextVQA: 84.3%, OCRBench: 84.2%. 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 LFM2.5-VL-3B and Qwen3 VL 30B A3B Thinking?

LFM2.5-VL-3B 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 LFM2.5-VL-3B and Qwen3 VL 30B A3B Thinking?

Key differences include LLM Stats Score (2.7 vs 17.8), licensing (LFM Open License v1.0 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes LFM2.5-VL-3B and Qwen3 VL 30B A3B Thinking?

LFM2.5-VL-3B is developed by Liquid AI and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.

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