Using Nous Hermes 2 Mixtral 8x7B on Fireworks AI
Implementation guide · Hermes 2 · Nous Research
ProvisionedOpen Source
Fireworks AI exposes Nous Hermes 2 Mixtral 8x7B through model ID nous-hermes2-mixtral-8x7b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-05-19. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
nous-hermes2-mixtral-8x7b— see the documentation for request format. - 3
Code Examples
Install
pip install openaiAPI key
FIREWORKS_API_KEYModel ID
nous-hermes2-mixtral-8x7bFireworks 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="nous-hermes2-mixtral-8x7b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.50 |
| Output tokens | $0.50 |
Capabilities
No model capability flags are currently sourced.
About Nous Hermes 2 Mixtral 8x7B
Mixtral MoE variant of Hermes trained on 1M+ GPT-4 entries for content generation and customer service. Available in quantized formats (GGUF, GPTQ, AWQ) for flexible deployment.
Model Specs
Released2023-12-12
Parameters8x7B
Context32k
ArchitectureMixture of Experts
Knowledge cutoff2023-12