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LFM2.5-2.6B vs Qwen3-235B-A22B-Thinking-2507

Qwen3-235B-A22B-Thinking-2507 leads the LLM Stats Score 28.1 to 19.0.

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

Which is better?

Qwen3-235B-A22B-Thinking-2507 leads the overall LLM Stats Score 28.1 to 19.0, ranking #135 overall.

In the 3 individual benchmarks reported for both models, Qwen3-235B-A22B-Thinking-2507 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 Qwen3-235B-A22B-Thinking-2507

  • overall performance matters — it scores 28.1 and ranks #135 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • 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
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
19.0
#208
28.1
#135
Reasoning
14.7
#228
28.4
#128
Agents
7.9
#135
11.4
#108
Cost, coverage & limits
Benchmark wins
0 of 3
3 of 3
Input price
— / M
$0.30 / M
Output price
— / M
$3.00 / M
Context window
—
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
LFM2.5-2.6B
Qwen3-235B-A22B-Thinking-2507
Tool use
2.0#170
10.8#119
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for LFM2.5-2.6B · 25 for Qwen3-235B-A22B-Thinking-2507

3 shared

LFM2.5-2.6B outperforms in 0 benchmarks, while Qwen3-235B-A22B-Thinking-2507 is better at 3 benchmarks (AIME 2025, LiveCodeBench v6, Multi-IF).

Qwen3-235B-A22B-Thinking-2507 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

232.3B diff

Qwen3-235B-A22B-Thinking-2507 has 232.3B more parameters than LFM2.5-2.6B, making it 8636.1% larger.

Liquid AI
LFM2.5-2.6B
2.7Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
235.0Bparameters
2.7B
LFM2.5-2.6B
235.0B
Qwen3-235B-A22B-Thinking-2507

Context Window

Maximum input and output token capacity

Only Qwen3-235B-A22B-Thinking-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Thinking-2507 specifies output context (131,072 tokens).

Liquid AI
LFM2.5-2.6B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Sun Sep 20 2026 • llm-stats.com

License

Usage and distribution terms

LFM2.5-2.6B is licensed under LFM Open License v1.0, while Qwen3-235B-A22B-Thinking-2507 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

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

LFM2.5-2.6B was released on 2026-08-04, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

LFM2.5-2.6B is 13 months newer than Qwen3-235B-A22B-Thinking-2507.

LFM2.5-2.6B

Aug 4, 2026

1 months ago

1.0yr newer
Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

1.2 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?Start an Issue discussion→

Judge for yourself.

Run your own prompts against LFM2.5-2.6B and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.

LFM2.5-2.6B
✓ Preferred
Qwen3-235B-A22B-Thinking-2507
Open in Playground

FAQ

Common questions about LFM2.5-2.6B vs Qwen3-235B-A22B-Thinking-2507.

Which is better, LFM2.5-2.6B or Qwen3-235B-A22B-Thinking-2507?

Qwen3-235B-A22B-Thinking-2507 leads the LLM Stats Score 28.1 to 19.0. LFM2.5-2.6B is made by Liquid AI and Qwen3-235B-A22B-Thinking-2507 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 Qwen3-235B-A22B-Thinking-2507 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%. Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%.

What are the context window sizes for LFM2.5-2.6B and Qwen3-235B-A22B-Thinking-2507?

LFM2.5-2.6B supports an unknown number of tokens and Qwen3-235B-A22B-Thinking-2507 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 Qwen3-235B-A22B-Thinking-2507?

Key differences include LLM Stats Score (19.0 vs 28.1), 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 Qwen3-235B-A22B-Thinking-2507?

LFM2.5-2.6B is developed by Liquid AI and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.

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