SmolLM or TinyLlama: which tiny model to choose
Both are tiny, both are Apache 2.0 with no commercial caveats, both are in Ollama and neither needs a GPU. SmolLM offers sizes from 135M to 3B, is listed as supporting Russian, and SmolLM3 adds reasoning and long context with the full training recipe published. TinyLlama is a single 1.1B model on the Llama 2 architecture trained on 3 trillion tokens, and the catalog marks it as not supporting Russian. SmolLM is newer, July 2025 against March 2024, so for a fresh project it is the more sensible starting point.
Comparison based on catalog data
| Parameter | SmolLM | TinyLlama |
|---|---|---|
| Category | Text | Text |
| Developer | Hugging Face, USA | TinyLlama (SUTD researchers), Singapore |
| Releases | Jul 2024 – Jul 2025 | Sep 2023 – Mar 2024 |
| Sizes | 135M – 3B | 1.1B |
| Hardware | Laptop | Laptop |
| Commercial use | Commercial use allowed | Commercial use allowed |
| License | Apache 2.0 | Apache 2.0 |
| Russian | Supported | Not supported |
| Ollama | Yes | Yes |
| Without GPU | Yes | Yes |
| Tasks |
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Choose SmolLM if
- You need Russian directly on the device, which SmolLM lists
- You want a size range from 135M to 3B for phones or embedded use
- The open training recipe matters for your own fine-tuning
Choose TinyLlama if
- You specifically need the Llama 2 architecture at 1.1B
- The model is for teaching or a quick prototype
- You already have a stack built around TinyLlama and switching costs more
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