Model reference · Synced 2025-04-29
Meta-Llama-3.1-8B-Instruct
Meta-Llama-3.1-8B-Instruct is an AI model from GitHub Models. 128K context window. Capabilities: reasoning, tool calling, open weights. Available on 7 providers. Cheapest listing: $0 input / $0 output per 1M tokens.
Quick facts
- Cheapest input: $0 per 1M tokens (GitHub Models)
- Cheapest output: $0 per 1M tokens
- Context window: 128K tokens
- Max output: 33K tokens
- Release date: 2024-07-23
- Knowledge cutoff: 2023-12
- Capabilities: reasoning, tool calling, open weights
- Provider count: 7
Provider pricing
Same model, different providers, different prices. Cheapest first.
| Provider | Input / 1M | Output / 1M | Context | Listed |
|---|---|---|---|---|
| GitHub Models | $0 | $0 | 128K | 2024-07-23 |
| Kilo Gateway | $0.02 | $0.05 | 16K | 2024-07-23 |
| Nebius Token Factory | $0.02 | $0.06 | 128K | 2024-07-23 |
| Helicone | $0.02 | $0.05 | 16K | 2024-07-23 |
| Weights & Biases | $0.22 | $0.22 | 128K | 2024-07-23 |
| Azure Cognitive Services | $0.3 | $0.61 | 128K | 2024-07-23 |
| Azure | $0.3 | $0.61 | 128K | 2024-07-23 |
Prices synced daily from models.dev + provider docs.
How to use this model
If you're picking Meta-Llama-3.1-8B-Instruct for a project, the three things that matter most:
- Compare it side-by-side with one or two alternatives in the live comparison tool. Pricing differences matter more than benchmarks at scale.
- Pick the cheapest provider that meets your latency / SLA need. Big spread across providers for the same weights.
- Re-evaluate every 3 months. Frontier prices drop fast; a model that's cheapest today may not be in a quarter.
Related models
FAQ
How much does Meta-Llama-3.1-8B-Instruct cost? $0 input / $0 output per 1M tokens at the cheapest listing. See the table above for other providers.
What is the context window? 128K tokens.
Which providers offer it? Weights & Biases, Kilo Gateway, Nebius Token Factory, Helicone, Azure Cognitive Services, Azure, GitHub Models.
Where do these numbers come from? models.dev + provider documentation, synced daily. About the data.