Hermes 3 Llama 3.2 3B — Hardware Requirements & GPU Compatibility
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Hermes 3 Llama 3.2 3B is a 3-billion parameter instruction-tuned model by Nous Research, fine-tuned from Meta's Llama 3.2 3B base. It applies the Hermes training methodology to a compact model, targeting strong instruction following and conversational quality at minimal hardware cost. Despite its small size, this model benefits from the Hermes fine-tuning approach that emphasizes system prompt adherence and structured output. It can run on GPUs with as little as 4GB of VRAM when quantized, making it suitable for lightweight local deployments and resource-constrained environments.
77.3K downloads
175 likesSpecifications
- Publisher
- Nous Research
- Family
- Llama 3
- Parameters
- 3B
- Architecture
- LlamaForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 128,256
- Release Date
- 2024-12-18
- License
- Llama 3 Community
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HuggingFace
How Much VRAM Does Hermes 3 Llama 3.2 3B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 6.5 GB | 21.3 GB | 6.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Hermes 3 Llama 3.2 3B?
BF16 · 6.5 GBHermes 3 Llama 3.2 3B (BF16) requires 6.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 9+ GB is recommended. Using the full 131K context window can add up to 14.8 GB, bringing total usage to 21.3 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Hermes 3 Llama 3.2 3B?
BF16 · 6.5 GB33 devices with unified memory can run Hermes 3 Llama 3.2 3B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Derivatives (3)
Frequently Asked Questions
- How much VRAM does Hermes 3 Llama 3.2 3B need?
Hermes 3 Llama 3.2 3B requires 6.5 GB of VRAM at BF16. Full 131K context adds up to 14.8 GB (21.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 3B × 16 bits ÷ 8 = 6 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 15.3 GB (at full 131K context)
VRAM usage by quantization
BF166.5 GBBF16 + full context21.3 GB- Can I run Hermes 3 Llama 3.2 3B on a Mac?
Hermes 3 Llama 3.2 3B requires at least 6.5 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 3 Llama 3.2 3B locally?
Yes — Hermes 3 Llama 3.2 3B can run locally on consumer hardware. At BF16 quantization it needs 6.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hermes 3 Llama 3.2 3B?
At BF16, Hermes 3 Llama 3.2 3B can reach ~446 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~100 tok/s. 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 ÷ 6.5 × 0.55 = ~446 tok/s
Estimated speed at BF16 (6.5 GB)
AMD Instinct MI300X~446 tok/sNVIDIA GeForce RTX 4090~100 tok/sNVIDIA H100 SXM~334 tok/sAMD Instinct MI250X~276 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 3.2 3B?
At BF16, the download is about 6.00 GB.