Nous Hermes Llama 2 13B on Replicate API

Name: Nous Hermes Llama 2 13B on Replicate API
Brand: Nous Research
Price: 0.10 USD

Hermes · Nous Research

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Last refreshed 2026-04-19. Next refresh: weekly.

Why use Nous Hermes Llama 2 13B on Replicate API?

Replicate API offers Nous Hermes Llama 2 13B with pay-as-you-go pricing at $0.10/1M input tokens. Replicate is a cloud-based platform that enables users to run machine learning models easily and efficiently.

Compare Nous Hermes Llama 2 13B across 3 providers to find the best fit for your use case

Input / 1M

$0.10

Output / 1M

$0.50

Cache

Not sourced

Batch

Not sourced

Setup recipe

Python + curl

Install

pip install replicate

Auth

export REPLICATE_API_TOKEN=...

Call

import replicate
output = replicate.run(
    "nous-hermes-llama2-13b",
    input={"prompt": "Hello"}

Model ID

nous-hermes-llama2-13b

Request example

import replicate

# reads REPLICATE_API_TOKEN from env
# nous-hermes-llama2-13b format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
    "nous-hermes-llama2-13b",
    input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))

Gotchas

Replicate uses "owner/model-name" format (e.g. "meta/meta-llama-3-8b-instruct") for the latest version, or "owner/model-name:version-sha" to pin to a specific version. The REST endpoint splits owner and model-name into the path: /v1/models/{owner}/{model-name}/predictions.
The examples expect REPLICATE_API_TOKEN; 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	$0.10
Output tokens	$0.50

Capabilities

Structured Outputs

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. Known for strong performance across various benchmarks, it is suitable for applications like chatbots, content generation, and code generation, while still acknowledging limitations such as data bias and handling of open-ended prompts.