Replicate API exposes Llama 3 70B through model ID meta/meta-llama-3-70b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-09-18. Next refresh: weekly.
Quick Start
- 1
- 2Use the Replicate API SDK or REST API to call
meta/meta-llama-3-70b— see the documentation for request format. - 3
Code Examples
pip install replicateREPLICATE_API_TOKENmeta/meta-llama-3-70bReplicate uses "owner/model-name" format (e.g. "meta/meta-llama-3-8b-instruct") for the latest version, or "owner/model-name:version-sha" to pin to a specific version. The REST endpoint splits owner and model-name into the path: /v1/models/{owner}/{model-name}/predictions.
import replicate
# reads REPLICATE_API_TOKEN from env
# meta/meta-llama-3-70b format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"meta/meta-llama-3-70b",
input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))Pricing on Replicate API
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.65 |
| Output tokens | $2.75 |
Capabilities
No model capability flags are currently sourced.
About Llama 3 70B
The Llama 3 70B model is a state-of-the-art large language model with 70 billion parameters, released by Meta on April 18, 2024. It's based on an auto-regressive transformer architecture and has been optimized for dialogue applications using supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF). The model supports an 8,000-token context length and has been trained on over 15 trillion tokens from public online sources. It excels in tasks such as conversational AI, text generation, and natural language understanding, outperforming many existing open-source chat models on industry benchmarks.