Hermes 4 70B GGUF — Hardware Requirements & GPU Compatibility
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6.3K downloads
9 likesSpecifications
- Publisher
- LM Studio Community
- Family
- Hermes
- Parameters
- 70B
- Release Date
- 2025-08-26
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HuggingFace
How Much VRAM Does Hermes 4 70B GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 154 GB | — | 140.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Hermes 4 70B GGUF?
BF16 · 154 GBHermes 4 70B GGUF (BF16) requires 154 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 201+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Hermes 4 70B GGUF?
BF16 · 154 GB4 devices with unified memory can run Hermes 4 70B GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Pro M2 Ultra (192 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Hermes 4 70B GGUF need?
Hermes 4 70B GGUF requires 154 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 70B × 16 bits ÷ 8 = 140 GB
KV Cache + Overhead ≈ 14 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF16154.0 GB- Can NVIDIA GeForce RTX 5090 run Hermes 4 70B GGUF?
No — Hermes 4 70B GGUF requires at least 154 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Hermes 4 70B GGUF on a Mac?
Hermes 4 70B GGUF requires at least 154 GB at BF16, 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 4 70B GGUF locally?
Yes — Hermes 4 70B GGUF can run locally on consumer hardware. At BF16 quantization it needs 154 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hermes 4 70B GGUF?
At BF16, Hermes 4 70B GGUF can reach ~19 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 ÷ 154.0 × 0.55 = ~19 tok/s
Estimated speed at BF16 (154 GB)
AMD Instinct MI300X~19 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Hermes 4 70B GGUF?
At BF16, the download is about 140.00 GB.
- Which GPUs can run Hermes 4 70B GGUF?
No single consumer GPU has enough VRAM to run Hermes 4 70B GGUF at BF16 (154 GB). Multi-GPU or professional hardware is required.
- Which devices can run Hermes 4 70B GGUF?
4 devices with unified memory can run Hermes 4 70B GGUF at BF16 (154 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.