Hugging Face: model lineup and pricing overview
Hugging Face model lineup with prices, context windows and average benchmark scores. Open model hub and inference platform.
What the data shows
Hugging Face has 14 models in the index. The average input price is $0.96 and the average output price is $4.63 per million tokens.
The strongest model by average score is smollm3-instruct. The cheapest by input price is SmolLM3 1.5B.
How to read the lineup
- Start with the best model for quality-sensitive work.
- Use the cheapest model for high-volume tasks.
- Check open-weight availability if self-hosting matters.
- Keep a second provider for fallback.
Hugging Face models
| # | Model | Input / 1M | Output / 1M | Context | Avg score |
|---|---|---|---|---|---|
| 1 | SmolLM3 Instruct | $1.69 | $8.67 | 8,192 | 63.6 |
| 2 | SmolLM3 | $1.71 | $8.86 | 8,192 | 63.1 |
| 3 | Zephyr | $1.61 | $6.84 | 8,192 | 62.8 |
| 4 | Zephyr Instruct | $1.66 | $6.50 | 4,096 | 62.4 |
| 5 | SmolLM3 Chat | $1.61 | $7.69 | 16,384 | 62.1 |
| 6 | Zephyr Chat | $1.49 | $8.02 | 4,096 | 61.3 |
| 7 | SmolLM3 Base | $1.38 | $7.55 | 16,384 | 60.4 |
| 8 | Zephyr Base | $1.26 | $6.45 | 4,096 | 59.5 |
| 9 | SmolLM3 7B | $0.19 | $1.03 | 16,384 | 44.3 |
| 10 | SmolLM3 8B | $0.21 | $0.76 | 32,768 | 44.0 |
| 11 | Zephyr 8B | $0.22 | $0.84 | 8,192 | 43.0 |
| 12 | Zephyr 7B | $0.23 | $0.93 | 32,768 | 42.5 |
| 13 | Zephyr 1.5B | $0.10 | $0.51 | 32,768 | 38.0 |
| 14 | SmolLM3 1.5B | $0.040 | $0.17 | 8,192 | 36.8 |
Methodology
This story uses the AI & LLM Index dataset: 600 models, 40 providers and 12 benchmarks. Prices are listed per million tokens. Scores are modelled estimates on a 0–100 scale and are not official benchmark results. Figures are rounded for readability.
Related
FAQ
What does the Hugging Face: model lineup and pricing overview data show?
Hugging Face model lineup with prices, context windows and average benchmark scores. Open model hub and inference platform.
Are the numbers official?
No. Prices and scores are compiled for this demo index. Benchmark values are modelled estimates, not official results. Verify figures with the provider or benchmark owner before making decisions.
How should I use this ranking?
Use it to form a shortlist. Check the specific model pages, compare price and context, and test the shortlist on your own examples before committing.