Model comparison
SmolLM3-3B vs o3
Capability radar, value bars, and side-by-side posture.
SmolLM3-3B
Not scored
value score
o3
93
value score
SmolLM3-3B ctx
—
o3 ctx
200K
Capability radar
Value · context · multimodal · openness · speed posture
Value head-to-head
- o393
Attribute tape
| Field | SmolLM3-3B | o3 |
|---|---|---|
| Developer | HuggingFaceTB | OpenAI |
| Context | — | 200K |
| Modalities | Text, Code | |
| Openness | — | Proprietary Model |
| Speed | — | — |
| Price | — | $10/1M in · $40/1M out |
| Value score | — | 93 |
| Summary | SmolLM3-3B is a 3-billion-parameter open-weight language model from Hugging Face's Smol models research line, designed for reasoning, multilingual use across six languages, and long-context tasks up to 128k tokens. It emphasizes full openness — releasing weights and training details — alongside a hybrid reasoning mode and instruct tuning trained on an 11.2-trillion-token curriculum. | OpenAI reasoning model focused on hard problems. |