Hermes 4 70B — Hardware Requirements & GPU Compatibility
ChatReasoningRoleplay
321 downloads
174 likesSpecifications
- Publisher
- Nous Research
- Family
- Hermes
- Parameters
- 70B
- Architecture
- LlamaForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 128,256
- Release Date
- 2025-09-02
- License
- Llama 3 Community
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HuggingFace
How Much VRAM Does Hermes 4 70B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 141.0 GB | 183.3 GB | 140.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Hermes 4 70B?
BF16 · 141.0 GBHermes 4 70B (BF16) requires 141.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 184+ GB is recommended. Using the full 131K context window can add up to 42.3 GB, bringing total usage to 183.3 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Hermes 4 70B?
BF16 · 141.0 GB4 devices with unified memory can run Hermes 4 70B, 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
Derivatives (1)
Frequently Asked Questions
- How much VRAM does Hermes 4 70B need?
Hermes 4 70B requires 141.0 GB of VRAM at BF16. Full 131K context adds up to 42.3 GB (183.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 70B × 16 bits ÷ 8 = 140 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
BF16141.0 GBBF16 + full context183.3 GB- Can NVIDIA GeForce RTX 5090 run Hermes 4 70B?
No — Hermes 4 70B requires at least 141.0 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Hermes 4 70B on a Mac?
Hermes 4 70B requires at least 141.0 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 locally?
Yes — Hermes 4 70B can run locally on consumer hardware. At BF16 quantization it needs 141.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hermes 4 70B?
At BF16, Hermes 4 70B can reach ~21 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 ÷ 141.0 × 0.55 = ~21 tok/s
Estimated speed at BF16 (141.0 GB)
AMD Instinct MI300X~21 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?
At BF16, the download is about 140.00 GB.
- Which GPUs can run Hermes 4 70B?
No single consumer GPU has enough VRAM to run Hermes 4 70B at BF16 (141.0 GB). Multi-GPU or professional hardware is required.
- Which devices can run Hermes 4 70B?
4 devices with unified memory can run Hermes 4 70B at BF16 (141.0 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.