Hermes-3-Llama-3.1-8B
meta-llamallama3text

Hermes-3-Llama-3.1-8B

Updated Oct 19, 2026
Parameters
8B
Context
131,072
License
llama3
Q4 GGUF
4.92 GB
Updated
Oct 19, 2026

Q4 GGUF download: NousResearch/Hermes-3-Llama-3.1-8B-GGUF - 4.92 GB on disk, read 2026-10-19. VRAM figures above are estimates; this is the actual file size.

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Runs on your 24 GB - best at FP16
4 of 4 quantizations fit Hermes-3-Llama-3.1-8B with real runtime overhead.
Q4_K_M
5 GB
Q5_K_M
6 GB
Q8_0
9 GB
FP16
16 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve NousResearch/Hermes-3-Llama-3.1-8B

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Deep dive

Notes, sources, and the full write-up

Hermes-3-Llama-3.1-8B is a 8B-parameter llama3 model from NousResearch. At Q4_K_M it needs roughly 5 GB of VRAM, placing it in the 8–12 GB GPU hardware tier.

Popularity

Hermes-3-Llama-3.1-8B has 492,635 downloads in the last month on HuggingFace and 519 likes.

Frequently asked

Quick answers to common questions

How much VRAM does Hermes-3-Llama-3.1-8B need?

Hermes-3-Llama-3.1-8B with 8B parameters needs approximately 5 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is Hermes-3-Llama-3.1-8B better than other meta-llama models?

Hermes-3-Llama-3.1-8B has 8B parameters with 131,072 context - a strong choice for general use.

What license is Hermes-3-Llama-3.1-8B under?

Hermes-3-Llama-3.1-8B is released under the llama3 license, making it suitable for most commercial and personal projects.

What hardware runs Hermes-3-Llama-3.1-8B well?

With 8B parameters, Hermes-3-Llama-3.1-8B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for Hermes-3-Llama-3.1-8B?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~6 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

How long can Hermes-3-Llama-3.1-8B's context window handle?

Hermes-3-Llama-3.1-8B supports a 131,072-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.

What models compete with Hermes-3-Llama-3.1-8B?

Hermes-3-Llama-3.1-8B competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec