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LFM2.5-2.6B vs Qwen3 VL 30B A3B Thinking

LFM2.5-2.6B and Qwen3 VL 30B A3B Thinking are closely matched at 19.0 and 18.3 on the LLM Stats Score.

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

Which is better?

LFM2.5-2.6B and Qwen3 VL 30B A3B Thinking are closely matched on the overall LLM Stats Score at 19.0 and 18.3.

In the 3 individual benchmarks reported for both models, Qwen3 VL 30B A3B Thinking wins 2; 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 LFM2.5-2.6B

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

Choose Qwen3 VL 30B A3B Thinking

  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results

At a glance

The differences that matter most.

Core performance indexes
19.0
#208
18.3
#213
14.7
#228
19.5
#199
7.9
#135
7.2
#136
Cost, coverage & limits
Benchmark wins
1 of 3
2 of 3
Input price
— / M
$0.20 / M
Output price
— / M
$0.99 / M
Context window
131,072

Individual benchmarks

9 reported for LFM2.5-2.6B · 50 for Qwen3 VL 30B A3B Thinking

3 shared

LFM2.5-2.6B outperforms in 1 benchmarks (Multi-IF), while Qwen3 VL 30B A3B Thinking is better at 2 benchmarks (AIME 2025, LiveCodeBench v6).

Qwen3 VL 30B A3B Thinking shows notably better performance in the majority of benchmarks.

Sun Sep 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

28.3B diff

Qwen3 VL 30B A3B Thinking has 28.3B more parameters than LFM2.5-2.6B, making it 1052.4% larger.

Liquid AI
LFM2.5-2.6B
2.7Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
2.7B
LFM2.5-2.6B
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
LFM2.5-2.6B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas LFM2.5-2.6B does not.

Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

LFM2.5-2.6B

Text
Images
Audio
Video

Qwen3 VL 30B A3B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

LFM2.5-2.6B 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.

LFM2.5-2.6B

LFM Open License v1.0

Open weights

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

LFM2.5-2.6B was released on 2026-08-04, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.

LFM2.5-2.6B is 11 months newer than Qwen3 VL 30B A3B Thinking.

LFM2.5-2.6B

Aug 4, 2026

1 months ago

10mo newer
Qwen3 VL 30B A3B Thinking

Sep 22, 2025

12 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?Start an Issue discussion

Judge for yourself.

Run your own prompts against LFM2.5-2.6B and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.

LFM2.5-2.6B
✓ Preferred
Qwen3 VL 30B A3B Thinking
Open in Playground

FAQ

Common questions about LFM2.5-2.6B vs Qwen3 VL 30B A3B Thinking.

Which is better, LFM2.5-2.6B or Qwen3 VL 30B A3B Thinking?

LFM2.5-2.6B and Qwen3 VL 30B A3B Thinking are closely matched on the LLM Stats Score at 19.0 and 18.3. LFM2.5-2.6B 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 LFM2.5-2.6B compare to Qwen3 VL 30B A3B Thinking in benchmarks?

LFM2.5-2.6B scores Multi-IF: 80.1%, PinchBench: 68.2%, Claw-Eval: 62.8%, LiveCodeBench v6: 59.4%, IFBench: 59.2%. 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 LFM2.5-2.6B and Qwen3 VL 30B A3B Thinking?

LFM2.5-2.6B 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 LFM2.5-2.6B and Qwen3 VL 30B A3B Thinking?

Key differences include LLM Stats Score (19.0 vs 18.3), multimodal support (no vs yes), licensing (LFM Open License v1.0 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes LFM2.5-2.6B and Qwen3 VL 30B A3B Thinking?

LFM2.5-2.6B is developed by Liquid AI and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.