Nous Research: Hermes 2 Pro - Llama-3 8B
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Hermes 2 Pro Llama 3 8B is an 8B parameter model fine-tuned on Meta's Llama 3, optimized for function calling (90% accuracy) and structured JSON outputs (84% accuracy). It features dedicated tool-call parsing tokens for agentic capabilities and outperforms Llama-3 8B Instruct on AGIEval, TruthfulQA, and BigBench benchmarks.
Context Window 8K
tokens
Max Output 8K
tokens
Input Cost $0.14
per million tokens
Output Cost $0.14
per million tokens
Release Date May 27, 2024
Code Example
Add AI to your app with the Puter.js AI API — no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
More AI Models From Nous Research
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Hermes 4 14B
Hermes 4 14B is the smallest model in Nous Research's Hermes 4 family, a fine-tune of Qwen3-14B trained on a post-training corpus of roughly 60B tokens built around verified reasoning traces. It is a hybrid reasoning model. It answers directly by default and can be switched into a reasoning mode that works through explicit think segments before the final answer, with training aimed at keeping those reasoning traces from running overlong. It is trained for function calling and tool use within a single assistant turn, and for structured outputs, including emitting schema-valid JSON and repairing malformed objects. In line with the Hermes series' focus on steerability and neutral alignment, Nous Research reports state-of-the-art results for Hermes 4 on its RefusalBench test, meaning fewer refused requests than comparable models.
ChatHermes 4 405B
Hermes 4 405B is a frontier hybrid-mode reasoning model based on Llama-3.1-405B, trained on a 60B token dataset with verified reasoning traces. It features toggleable deep reasoning via think tags, massive improvements in math, code, STEM, and logic, and achieves state-of-the-art on RefusalBench for reduced censorship.
ChatHermes 4 70B
Hermes 4 70B is a hybrid reasoning model based on Llama-3.1-70B with toggleable deep thinking mode using think tags. It offers major improvements in math, code, STEM, logic, and creative writing while supporting JSON schema adherence, function calling, and reduced refusal rates compared to other models.
Frequently Asked Questions
You can access Hermes 2 Pro - Llama-3 8B by Nous Research through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Hermes 2 Pro - Llama-3 8B to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.14 |
| Output | $0.14 |
Hermes 2 Pro - Llama-3 8B was created by Nous Research and released on May 27, 2024.
Hermes 2 Pro - Llama-3 8B supports a context window of 8K tokens. For reference, that is roughly equivalent to 16 pages of text.
Hermes 2 Pro - Llama-3 8B can generate up to 8K tokens in a single response.
Yes — the Hermes 2 Pro - Llama-3 8B API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
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