Using OpenHermes 2.5 Mistral 7B on Fireworks AI
Implementation guide · OpenHermes 2 · Teknium
Fireworks AI exposes OpenHermes 2.5 Mistral 7B through model ID accounts/fireworks/models/openhermes-2p5-mistral-7b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-15. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
accounts/fireworks/models/openhermes-2p5-mistral-7b— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/openhermes-2p5-mistral-7bFireworks 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/openhermes-2p5-mistral-7b",
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 OpenHermes 2.5 Mistral 7B
OpenHermes 2.5 Mistral 7B is an advanced large language model developed by Teknium, building on the previous version, OpenHermes 2. Utilizing a transformer architecture, it's fine-tuned on over one million entries, combining code and non-code data, primarily composed of GPT-4 generated text. This enhances its human-like response capabilities across diverse contexts. It excels in conversational AI with its multi-turn dialogue support through the ChatML format, significantly improves in code generation tasks with a high HumanEval score, and performs robustly on benchmarks like GPT4All and AGIEval.