Hermes 3 Llama 3.1 70B — Hardware Requirements & GPU Compatibility
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Hermes 3 Llama 3.1 70B is a 70.6B-parameter open language model from Nous Research in the Llama 3 family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 43.30 GB of VRAM — see which GPUs and Macs can run it below.
131.8K downloads
126 likesSpecifications
- Publisher
- Nous Research
- Family
- Llama 3
- Parameters
- 70.6B
- Architecture
- LlamaForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 128,256
- Release Date
- 2024-07-29
- License
- Llama 3 Community
Get Started
HuggingFace
How Much VRAM Does Hermes 3 Llama 3.1 70B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 31.0 GB | 73.2 GB | 29.99 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 31.8 GB | 74.1 GB | 30.87 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 35.4 GB | 77.6 GB | 34.39 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 43.3 GB | 85.6 GB | 42.33 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 51.2 GB | 93.5 GB | 50.27 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 59.2 GB | 101.5 GB | 58.21 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 71.5 GB | 113.8 GB | 70.55 GB | 8-bit quantization, near-lossless |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Hermes 3 Llama 3.1 70B?
Q4_K_M · 43.3 GBHermes 3 Llama 3.1 70B (Q4_K_M) requires 43.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 57+ GB is recommended. Using the full 131K context window can add up to 42.3 GB, bringing total usage to 85.6 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Hermes 3 Llama 3.1 70B?
Q4_K_M · 43.3 GB11 devices with unified memory can run Hermes 3 Llama 3.1 70B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Where to Download Hermes 3 Llama 3.1 70B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does Hermes 3 Llama 3.1 70B need?
Hermes 3 Llama 3.1 70B requires 43.3 GB of VRAM at Q4_K_M, or 142.1 GB at BF16. Full 131K context adds up to 42.3 GB (85.6 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 70.6B × 4.8 bits ÷ 8 = 42.3 GB
KV Cache + Overhead ≈ 1 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 43.3 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M43.3 GBQ4_K_M + full context85.6 GB- Can NVIDIA GeForce RTX 4090 run Hermes 3 Llama 3.1 70B?
Yes, at IQ2_XS (22.1 GB) or lower. Higher quantizations like IQ2_M (24.8 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Hermes 3 Llama 3.1 70B?
For Hermes 3 Llama 3.1 70B, Q4_K_M (43.3 GB) offers the best balance of quality and VRAM usage. Q4_K_L (44.2 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 20.4 GB.
VRAM requirement by quantization
IQ2_XXS20.4 GBQ2_K31.0 GBQ3_K_L37.1 GBQ4_K_M ★43.3 GBQ4_K_L44.2 GBBF16142.1 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Hermes 3 Llama 3.1 70B on a Mac?
Hermes 3 Llama 3.1 70B requires at least 20.4 GB at IQ2_XXS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Hermes 3 Llama 3.1 70B locally?
Yes — Hermes 3 Llama 3.1 70B can run locally on consumer hardware. At Q4_K_M quantization it needs 43.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hermes 3 Llama 3.1 70B?
At Q4_K_M, Hermes 3 Llama 3.1 70B can reach ~67 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 43.3 × 0.55 = ~67 tok/s
Estimated speed at Q4_K_M (43.3 GB)
~67 tok/s~50 tok/s~42 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Hermes 3 Llama 3.1 70B?
At Q4_K_M, the download is about 42.33 GB. The full-precision BF16 version is 141.11 GB. The smallest option (IQ2_XXS) is 19.40 GB.
- Which GPUs can run Hermes 3 Llama 3.1 70B?
No single consumer GPU has enough VRAM to run Hermes 3 Llama 3.1 70B at Q4_K_M (43.3 GB). Multi-GPU or professional hardware is required.
- Which devices can run Hermes 3 Llama 3.1 70B?
11 devices with unified memory can run Hermes 3 Llama 3.1 70B at Q4_K_M (43.3 GB), including Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.