Hermes 4 14B — Hardware Requirements & GPU Compatibility
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Hermes 4 14B is a 424960-parameter open language model from Nous Research in the Hermes family. It supports a context window of up to 40,960 tokens. At Q4_K_M it needs about 0.64 GB of VRAM — see which GPUs and Macs can run it below.
37.3K downloads
152 likesSpecifications
- Publisher
- Nous Research
- Family
- Hermes
- Parameters
- 424960
- Architecture
- Qwen3ForCausalLM
- Context Length
- 40,960 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2026-01-09
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Hermes 4 14B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 0.6 GB | 7.0 GB | 0.00 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 0.6 GB | 7.0 GB | 0.00 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 0.6 GB | 7.0 GB | 0.00 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 0.6 GB | 7.0 GB | 0.00 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 0.6 GB | 7.0 GB | 0.00 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 0.6 GB | 7.0 GB | 0.00 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 0.6 GB | 7.0 GB | 0.00 GB | 8-bit quantization, near-lossless |
| Q4_0 | 4.00 | 0.6 GB | 7.0 GB | 0.00 GB | 4-bit legacy quantization |
Which GPUs Can Run Hermes 4 14B?
Q4_K_M · 0.6 GBHermes 4 14B (Q4_K_M) requires 0.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1+ GB is recommended. Using the full 41K context window can add up to 6.4 GB, bringing total usage to 7.0 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Hermes 4 14B?
Q4_K_M · 0.6 GB33 devices with unified memory can run Hermes 4 14B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Derivatives (2)
Frequently Asked Questions
- How much VRAM does Hermes 4 14B need?
Hermes 4 14B requires 0.6 GB of VRAM at Q4_K_M, or 0.6 GB at Q5_K_L. Full 41K context adds up to 6.4 GB (7.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 424960 × 4.8 bits ÷ 8 = 0 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 7 GB (at full 41K context)
VRAM usage by quantization
Q4_K_M0.6 GBQ4_K_M + full context7.0 GB- What's the best quantization for Hermes 4 14B?
For Hermes 4 14B, Q4_K_M (0.6 GB) offers the best balance of quality and VRAM usage. Q5_K_S (0.6 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 0.6 GB.
VRAM requirement by quantization
Q2_K0.6 GBIQ4_XS0.6 GBQ4_K_M ★0.6 GBQ8_00.6 GBIQ3_M0.6 GBQ5_K_L0.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Hermes 4 14B on a Mac?
Hermes 4 14B requires at least 0.6 GB at Q2_K, 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 14B locally?
Yes — Hermes 4 14B can run locally on consumer hardware. At Q4_K_M quantization it needs 0.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hermes 4 14B?
At Q4_K_M, Hermes 4 14B can reach ~4555 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~1024 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 ÷ 0.6 × 0.55 = ~4555 tok/s
Estimated speed at Q4_K_M (0.6 GB)
~4555 tok/s~1024 tok/s~3404 tok/s~2816 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 14B?
At Q4_K_M, the download is about 0.00 GB. The full-precision Q5_K_L version is 0.00 GB. The smallest option (Q2_K) is 0.00 GB.
- Which GPUs can run Hermes 4 14B?
35 consumer GPUs can run Hermes 4 14B at Q4_K_M (0.6 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Hermes 4 14B?
33 devices with unified memory can run Hermes 4 14B at Q4_K_M (0.6 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.