Compare / LFM2.5 1.2B Instruct vs Qwen3.5 0.8B

LFM2.5 1.2B Instruct vs Qwen3.5 0.8B

Updated November 2026

Verdict

LFM2.5 1.2B Instruct scores higher on the Small LM Index: 20.6 vs 10.7. On the 5 benchmarks both labs report, LFM2.5 1.2B Instruct wins 5 and Qwen3.5 0.8B wins 0. Both need about 1.3 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.

Pick LFM2.5 1.2B Instruct if…

  • you want the strongest model overall
  • you need precise instruction following
  • you build agents that call tools

Pick Qwen3.5 0.8B if…

  • you work with long documents
  • you need a permissive license (Apache-2.0)
  • you need image input
  • you want the more widely used model (more quantized builds and community support)

Specifications

LFM2.5 1.2B InstructQwen3.5 0.8B
Small LM Index20.6 (likely 18–24)10.7 (likely 9–13)
LabLiquid AI · United StatesAlibaba (Qwen) · China
Released2026-01-062026-03-02
Parameters1.2B (dense)900M (dense)
Memory at 4-bit~1.3 GB~1.2 GB
Context window32K tokens262K tokens
Inputtexttext, image, video
ReasoningNo thinkingHybrid (thinking on/off)
LicenseLFM Open LicenseApache-2.0
API price / 1M tokensSelf-host onlySelf-host only
Hugging Face downloads (30 days)122.7K3.7M

Benchmarks

Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.

BenchmarkLFM2.5 1.2B InstructQwen3.5 0.8B
MMLU-Pro Knowledge44.442.3
GPQA Diamond Knowledge38.911.9
AIME Math14.0≈ 4
τ²-Bench Agentic—11.6
IFBench Instruction following47.321.0
MMMU-Pro Vision—25.8✓
MMLU Knowledge—59.5
Multilingual MMLU Multilingual—44.3
IFEval Instruction following86.244.0
BFCL Agentic49.125.3
AA-LCR Long context—4.7

Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.

Questions

Which is better, LFM2.5 1.2B Instruct or Qwen3.5 0.8B?

LFM2.5 1.2B Instruct scores higher on the Small LM Index: 20.6 vs 10.7. On the 5 benchmarks both labs report, LFM2.5 1.2B Instruct wins 5 and Qwen3.5 0.8B wins 0.

Which is cheaper to run?

Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 1.3 GB of memory at 4-bit quantization.

Which has the longer context window?

Qwen3.5 0.8B has the longer context window: 262K tokens against 32K.

Can I use LFM2.5 1.2B Instruct and Qwen3.5 0.8B commercially?

LFM2.5 1.2B Instruct is released under LFM Open License and Qwen3.5 0.8B under Apache-2.0. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.

Related comparisons