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LFM2.5-2.6B vs Qwen3.5-9B

LFM2.5-2.6B and Qwen3.5-9B are closely matched at 19.0 and 24.7 on the LLM Stats Score.

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

Which is better?

LFM2.5-2.6B and Qwen3.5-9B are closely matched on the overall LLM Stats Score at 19.0 and 24.7.

In the 3 individual benchmarks reported for both models, Qwen3.5-9B wins 3; 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 Qwen3.5-9B

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

At a glance

The differences that matter most.

LFM2.5-2.6B
Liquid AI
Qwen3.5-9B
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
19.0
#208
24.7
#160
Reasoning
14.7
#228
24.4
#156
Agents
7.9
#135
8.4
#131
Cost, coverage & limits
Benchmark wins
0 of 3
3 of 3
Input price
— / M
$0.10 / M
Output price
— / M
$0.15 / M
Context window
—
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
LFM2.5-2.6B
Qwen3.5-9B
Tool use
2.0#170
10.0#130
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for LFM2.5-2.6B · 25 for Qwen3.5-9B

3 shared

LFM2.5-2.6B outperforms in 0 benchmarks, while Qwen3.5-9B is better at 3 benchmarks (BFCL-V4, IFBench, LiveCodeBench v6).

Qwen3.5-9B significantly outperforms across most benchmarks.

Sun Sep 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

6.3B diff

Qwen3.5-9B has 6.3B more parameters than LFM2.5-2.6B, making it 234.6% larger.

Liquid AI
LFM2.5-2.6B
2.7Bparameters
Alibaba Cloud / Qwen Team
Qwen3.5-9B
9.0Bparameters
2.7B
LFM2.5-2.6B
9.0B
Qwen3.5-9B

Context Window

Maximum input and output token capacity

Only Qwen3.5-9B specifies input context (262,144 tokens). Only Qwen3.5-9B specifies output context (262,144 tokens).

Liquid AI
LFM2.5-2.6B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3.5-9B
Input262,144 tokens
Output262,144 tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.5-9B supports multimodal inputs, whereas LFM2.5-2.6B does not.

Qwen3.5-9B 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

Qwen3.5-9B

Text
Images
Audio
Video

License

Usage and distribution terms

LFM2.5-2.6B is licensed under LFM Open License v1.0, while Qwen3.5-9B 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

Qwen3.5-9B

Apache 2.0

Open weights

Release Timeline

When each model was launched

LFM2.5-2.6B was released on 2026-08-04, while Qwen3.5-9B was released on 2026-03-02.

LFM2.5-2.6B is 5 months newer than Qwen3.5-9B.

LFM2.5-2.6B

Aug 4, 2026

1 months ago

5mo newer
Qwen3.5-9B

Mar 2, 2026

6 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 Qwen3.5-9B side-by-side, then vote on the output you prefer.

LFM2.5-2.6B
✓ Preferred
Qwen3.5-9B
Open in Playground

FAQ

Common questions about LFM2.5-2.6B vs Qwen3.5-9B.

Which is better, LFM2.5-2.6B or Qwen3.5-9B?

LFM2.5-2.6B and Qwen3.5-9B are closely matched on the LLM Stats Score at 19.0 and 24.7. LFM2.5-2.6B is made by Liquid AI and Qwen3.5-9B 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 Qwen3.5-9B 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%. Qwen3.5-9B scores IFEval: 91.5%, MMLU-Redux: 91.1%, C-Eval: 88.2%, MAXIFE: 83.4%, Global PIQA: 83.2%.

What are the context window sizes for LFM2.5-2.6B and Qwen3.5-9B?

LFM2.5-2.6B supports an unknown number of tokens and Qwen3.5-9B 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 LFM2.5-2.6B and Qwen3.5-9B?

Key differences include LLM Stats Score (19.0 vs 24.7), 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 Qwen3.5-9B?

LFM2.5-2.6B is developed by Liquid AI and Qwen3.5-9B is developed by Alibaba Cloud / Qwen Team.

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