Fireworks AI exposes Llama 2 13B through model ID accounts/fireworks/models/llama-v2-13b. 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-v2-13b— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/llama-v2-13bFireworks 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-v2-13b",
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 2 13B
The Llama 2 13B model is a mid-sized variant in Meta's Llama 2 family of large language models, featuring 13 billion parameters. It utilizes an optimized transformer architecture and was trained on 2 trillion tokens from public sources. The model incorporates supervised fine-tuning and reinforcement learning with human feedback, making it suitable for various NLP tasks, including text generation and interactive AI systems. It has demonstrated competitive performance against both open-source and closed-source models in terms of helpfulness and safety.