llama-3-70b

llama-3-70b is a efficient-tier language model from Meta with 70B parameters. llama-3-70b is an open-weights model, meaning the weights are publicly available for self-hosting, fine-tuning, and deployment on your own infrastructure — not just through Meta's API. Llama 3 is Meta's open-weights model family, available in 8B and 70B sizes — the most widely deployed open-weights models, with strong community support and broad framework compatibility.

llama-3-70b is priced at $0.51/1M input tokens and $0.74/1M output tokens. Output tokens are 1.5× more expensive than input tokens — this ratio reflects the sequential nature of autoregressive generation, which requires a separate forward pass per output token versus parallel processing of all input tokens simultaneously. At a typical usage pattern of 1,000 input tokens and 500 output tokens per call, llama-3-70b costs approximately $0.88 per 1,000 API calls. Meta does not publish a prompt caching rate for this model, so repeated long contexts are billed at the standard $0.51/1M input rate.

Its 8K-token context window is standard for this tier — adequate for most chat and completion tasks, but may require chunking for long-document workloads. Median latency (P50 time-to-first-token) is approximately 400ms — suitable for interactive applications where sub-second response is acceptable. Throughput is approximately 90 tokens/second — adequate for streaming at comfortable reading speed. Maximum output length is 4K tokens — adequate for most generation tasks including essays, code functions, and detailed responses.

llama-3-70b is best suited to chat, coding, cost. Supported capabilities include streaming token output for real-time UIs. When evaluating this model for a specific workload, the most important factors are: context window (does your input fit?), output price (how long are your generations?), and latency (is this interactive or batch?). The pricing table above shows how llama-3-70b compares to similar models across these dimensions.

llama-3-70b sits in the efficient tier — optimized for speed and cost while maintaining solid quality, ideal for high-volume or latency-sensitive workloads. As an open-weights model, llama-3-70b can be self-hosted on GPU compute (see the GPU rental comparison on this site) to eliminate per-token API costs entirely — the break-even point versus API pricing depends on your volume and the GPU hourly rate. When comparing llama-3-70b to alternatives, use the similar models section on this page to find models at comparable price points with different capability tradeoffs. The intelligence score (64/100) reflects aggregate benchmark performance — a useful proxy for general capability, though real-world performance varies significantly by task type. Always test with your specific prompts and use case before committing to a model for production.