[whatmodel.sh](../../README.md) / Hermes 2 Pro Llama 3 8B
# Hermes 2 Pro Llama 3 8B
Nous Research · released 2024-04 · 8.03B params · llama3
**score 47.3** ±2.9 · #423 of 732 · from 3 benchmark results across 3 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Hermes 2 Pro Llama 3 8B among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃●█▄▅▅▄▄▂▁ #280 of 313* 20% 1
agent tasks · #280 of 313 · 20% of its score
Beats [Magistral Small 1.0 (2506)](magistral-small-2506.md), [Llama 4 Scout (109B-A17B)](llama-4-scout.md), [Bielik 11B v2.3 Instruct](bielik-11b-v2-3-instruct.md) here, though they rank higher overall. Trails [Qwen3 0.6B](qwen3-0-6b.md), [Qwen2.5 1.5B Instruct](qwen2-5-1-5b.md), [Granite 4.0 H 1B](granite-4-0-h-1b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
BFCL v3 46.8% ▁▁▁▁▁▃●█▅▄▁▁ beats 27/114 medium · avg 51% 20% blunt · at its level
other tests (2)
test result vs the others in its run difficulty counts why
Polish EQ-Bench v2 (SpeakLeash) 54.6% ▁··▁▁▂▂▆●▆█▆ beats 29/70 medium · avg 62% 55% at its level
Open PT-LLM Leaderboard average (… 69.4% ▃▁▁▁▁▁▁▁▂●▅▁ beats 161/276 medium · avg 72% 21% at its level · noisy
source results share of the score
SpeakLeash Polish EQ-Bench leaderboard 1 55% ▇▇▇▇▇▇▇
Open Portuguese LLM Leaderboard 1 21% ▇▇▇
Berkeley Function Calling Leaderboard r… 1 20% ▇▇
prior: pull toward the middle 4% ▇
weighted average = 47.3
Licences: SpeakLeash Polish EQ-Bench leaderboard ([Apache-2.0](../../licenses/hf-leaderboard-spaces-Apache-2.0.txt)) · Open Portuguese LLM Leaderboard ([Apache-2.0](../../licenses/hf-leaderboard-spaces-Apache-2.0.txt)) · Berkeley Function Calling Leaderboard result archive ([Apache-2.0](../../licenses/bfcl-result-archive-v4-Apache-2.0.txt))
## How to run it
### llama.cpp (recommended)
1. Install llama.cpp. Homebrew and winget installs name the commands llama-cli and llama-server instead. [Other ways to install](https://github.com/ggml-org/llama.cpp/blob/master/docs/install.md)
```sh
# macOS / Linux
curl -LsSf https://llama.app/install.sh | sh
# Windows
irm https://llama.app/install.ps1 | iex
```
2. Run Hermes 2 Pro Llama 3 8B (Q4_K_M, needs ~4.9 GB, from [huggingface.co/second-state](https://huggingface.co/second-state/Hermes-2-Pro-Llama-3-8B-GGUF/tree/79b04e32693d77068a8244da59a778fc799e1d01))
```sh
llama cli -hf second-state/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf second-state/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M
```
Other versions: Q8_0 (~8.5 GB) `llama cli -hf second-state/Hermes-2-Pro-Llama-3-8B-GGUF:Q8_0`
### LM Studio
1. Install LM Studio. Open the app once before using the lms command. [Download it (macOS / Windows / Linux)](https://lmstudio.ai/download)
2. Run Hermes 2 Pro Llama 3 8B (Q4_K_M, needs ~4.9 GB, from [huggingface.co/second-state](https://huggingface.co/second-state/Hermes-2-Pro-Llama-3-8B-GGUF/tree/79b04e32693d77068a8244da59a778fc799e1d01))
```sh
lms get https://huggingface.co/second-state/Hermes-2-Pro-Llama-3-8B-GGUF@Q4_K_M -y
```
3. Then run lms ls to see its name, and lms chat followed by that name
Other versions: Q8_0 (~8.5 GB) `lms get https://huggingface.co/second-state/Hermes-2-Pro-Llama-3-8B-GGUF@Q8_0 -y`
### Ollama
1. Install Ollama. [Download it (macOS / Windows)](https://ollama.com/download)
```sh
# Linux
curl -fsSL https://ollama.com/install.sh | sh
```
2. Run Hermes 2 Pro Llama 3 8B (Q4_K_M, needs ~4.9 GB, from [huggingface.co/second-state](https://huggingface.co/second-state/Hermes-2-Pro-Llama-3-8B-GGUF/tree/79b04e32693d77068a8244da59a778fc799e1d01))
```sh
ollama run hf.co/second-state/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M
```
Other versions: Q8_0 (~8.5 GB) `ollama run hf.co/second-state/Hermes-2-Pro-Llama-3-8B-GGUF:Q8_0`
### Other ways to run it
1. Run it as published (fp16, needs ~16.06 GB, from [huggingface.co/NousResearch](https://huggingface.co/NousResearch/Hermes-2-Pro-Llama-3-8B/tree/f798274b30e7d2d4797c369edcc0cc7473b6e6f2))
```sh
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='NousResearch/Hermes-2-Pro-Llama-3-8B', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"
```
Model repository and documentation: [huggingface.co/NousResearch](https://huggingface.co/NousResearch/Hermes-2-Pro-Llama-3-8B)
[interactive version](https://whatmodel.sh/model/hermes-2-pro-llama-3-8b) · [JSON](https://whatmodel.sh/api?format=json&all=1)