Compare / LFM2.5 2.6B vs SmolLM3 3B

LFM2.5 2.6B vs SmolLM3 3B

Updated November 2026

Verdict

LFM2.5 2.6B scores higher on the Small LM Index: 43.2 vs 30.4. On the 4 benchmarks both labs report, LFM2.5 2.6B wins 4 and SmolLM3 3B wins 0. Both need about 3 GB of memory at 4-bit quantization. Only LFM2.5 2.6B has a hosted API on OpenRouter ($0.39 per million tokens); the other has to be self-hosted.

Pick LFM2.5 2.6B if…

  • you want the strongest model overall
  • you mostly write code
  • you need math and reasoning
  • you need precise instruction following
  • you want a hosted API rather than running it yourself
  • you work with long documents

Pick SmolLM3 3B if…

  • you need a permissive license (Apache-2.0)
  • you want the more widely used model (more quantized builds and community support)

Specifications

LFM2.5 2.6BSmolLM3 3B
Small LM Index43.2 (likely 39–48)30.4 (likely 27–35)
LabLiquid AI · United StatesHugging Face (SmolLM) · Europe
Released2026-07-282025-07-08
Parameters2.7B (dense)3.1B (dense)
Memory at 4-bit~2.3 GB~3 GB
Context window128K tokens64K tokens
Inputtexttext
ReasoningNo thinkingHybrid (thinking on/off)
LicenseLFM Open LicenseApache-2.0
API price / 1M tokens$0.39 ($0.35 in, $0.50 out)Self-host only
Hugging Face downloads (30 days)69K567.6K

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 2.6BSmolLM3 3B
GPQA Diamond Knowledge57.841.7
Humanity's Last Exam Reasoning5.9≈ 2
AIME Math51.936.7
LiveCodeBench Coding59.430.0
SWE-bench Verified Coding18.0≈ 12
IFBench Instruction following59.2—
Multilingual MMLU Multilingual—64.1
IFEval Instruction following95.471.2
BFCL Agentic56.9—

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 2.6B or SmolLM3 3B?

LFM2.5 2.6B scores higher on the Small LM Index: 43.2 vs 30.4. On the 4 benchmarks both labs report, LFM2.5 2.6B wins 4 and SmolLM3 3B wins 0.

Which is cheaper to run?

Only LFM2.5 2.6B has a hosted API on OpenRouter ($0.39 per million tokens); the other has to be self-hosted. Both need about 3 GB of memory at 4-bit quantization.

Which has the longer context window?

LFM2.5 2.6B has the longer context window: 128K tokens against 64K.

Can I use LFM2.5 2.6B and SmolLM3 3B commercially?

LFM2.5 2.6B is released under LFM Open License and SmolLM3 3B 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.

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