OpenHermes

High-quality instruction-tuned Mistral model — tops leaderboards through superior training data quality.

LLMs & Chat Open Source Has API Open Source
Researched · Published · Reviewed
RECATOOLS Score
5.9 / 10
Capability
5
Value for money
8
Ease of use
5
ASEAN readiness
7
API quality
Founded
2023
HQ
Remote
Users
500k+ downloads
Launched
Nov 2023
Developer
Nous Research

Overview

OpenHermes is a series of open-source instruction-tuned models from Nous Research, fine-tuned primarily from Mistral base models using a curated dataset of high-quality synthetic and human-generated instruction data. The OpenHermes 2.5 variant, released in November 2023, achieved state-of-the-art results among 7B models on multiple open-source benchmarks and became widely adopted for its practical task performance.

The training dataset is the key differentiator: Nous Research assembled diverse, high-quality instructions from multiple sources including GPT-4 conversations, code data, mathematics, function calling, and multilingual content. This carefully curated mixture produces a model that performs well across a broad range of tasks rather than excelling narrowly.

OpenHermes 2.5 became one of the most downloaded instruction models on Hugging Face in late 2023 and early 2024, used in applications ranging from chatbots to RAG systems. Its strong function calling capability (important for tool-using agents) and practical performance across tasks made it the default recommendation for many 7B model use cases until Llama 3 and Mistral v0.3 were released.

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Pricing

Pricing shown for reference only. These figures reflect RECATOOLS research as of 8 May 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.

Free
Free
Fully free

Use cases

Building a function-calling AI agent with a small open-source model Deploying a capable 7B instruction model for production chatbot use Research into synthetic instruction data quality and its effect on model performance
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ASEAN Perspective

OpenHermes in Southeast Asia

ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).

RECATOOLS Verdict

OpenHermes 2.5 (Mistral-7B) by Teknium is a widely respected open fine-tune that became a go-to general-purpose 7B model, noted for solid instruction-following, conversation and a notable coding bump from its training mix. For a small self-hostable model it was a community favourite and a strong base for further tuning.

It suits hobbyists, fine-tuners and developers running local assistants on modest hardware. Caveats: it is a 2023-era model and the open ecosystem has moved on — newer Nous, Qwen and Llama fine-tunes generally outperform it now — so it is more of a proven baseline than a frontier choice. It is a model on Hugging Face, not a service, so there is no first-party API. Free, open, globally usable for self-hosting.

Independent AI-assisted assessment by RECATOOLS.

Notable facts

  • OpenHermes 2.5 was one of the top 3 most downloaded language models on Hugging Face in December 2023, driven by its practical utility across a wide range of tasks.
  • The model's function calling capability was specifically trained on data that teaches the model to invoke external tools correctly — critical for building AI agents.
  • OpenHermes was produced entirely by volunteer researchers in the Nous Research community, with no institutional funding.

Frequently asked questions

Is OpenHermes free?
Yes. Apache 2.0 licence — fully permissive for commercial use.
What base model is OpenHermes built on?
Mistral 7B, fine-tuned with the Hermes instruction dataset.
Is OpenHermes good for function calling?
Yes. OpenHermes 2.5 has strong function calling capability for building AI agents.
How does OpenHermes differ from Zephyr?
OpenHermes has a broader training dataset and stronger function calling. Zephyr uses DPO for better helpfulness alignment.
What is the OpenHermes training dataset?
A curated mixture of GPT-4 conversations, code, math, function calling data, and other high-quality instruction sources.

About this listing

Researched on
Published on
Last reviewed

This entry was compiled from publicly available data including OpenHermes's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with OpenHermes unless explicitly stated.

Data accuracy

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