Last refreshed 2026-04-19. Next refresh: weekly.
Why use Nous Hermes Llama 2 13B on Fireworks AI?
Fireworks AI offers Nous Hermes Llama 2 13B with pay-as-you-go pricing at $0.20/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Compare Nous Hermes Llama 2 13B across 3 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport FIREWORKS_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],accounts/fireworks/models/nous-hermes-llama2-13bRequest example
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/nous-hermes-llama2-13b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/nous-hermes-llama2-13b", not the LLMReference slug "nous-hermes-llama2-13b".
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Compare Nous Hermes Llama 2 13B Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Together AI | $0.30 | $0.30 |
| Fireworks AI | $0.20 | $0.20 |
| Replicate API | $0.10 | $0.50 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
About Nous Hermes Llama 2 13B
The Nous Hermes Llama 2 13B is an advanced large language model fine-tuned on over 300,000 instructions, building upon the Llama 2 architecture. Developed by Nous Research with contributions from Teknium, Emozilla, and compute sponsorship from Redmond AI, the model boasts features like extended response generation, reduced hallucinations, and compatibility with Alpaca prompt format. It is trained on a diverse dataset, including synthetic GPT-4 outputs, enhancing its knowledge and task completion capabilities.