Fireworks AI exposes Llama 3 8B through model ID accounts/fireworks/models/llama-v3-8b. 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 Fireworks AI SDK or REST API to call
accounts/fireworks/models/llama-v3-8b— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/llama-v3-8bFireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/llama-v3-8b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
No model capability flags are currently sourced.
About Llama 3 8B
The Llama 3 8B model, released on April 18, 2024, is Meta's latest large language model featuring 8 billion parameters. It's an auto-regressive transformer optimized for text generation and dialogue applications, particularly suited for assistant-like interactions. Trained on over 15 trillion tokens from diverse public sources, it incorporates advanced techniques like supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF). This model is designed to outperform many existing open-source chat models on industry benchmarks, emphasizing helpfulness and safety in its outputs. It's available for commercial and research use in English through the Hugging Face platform .