Hy3 — Hardware Requirements & GPU Compatibility
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Hy3 is a 298.8B-parameter open language model from Tencent in the Hunyuan 3 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 179.91 GB of VRAM — see which GPUs and Macs can run it below.
13.7K downloads
840 likesSpecifications
- Publisher
- Tencent
- Family
- Hunyuan 3
- Parameters
- 298.8B
- Architecture
- HYV3ForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 120,832
- Release Date
- 2026-07-02
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Hy3 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 127.6 GB | 170.2 GB | 126.98 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 131.3 GB | 174.0 GB | 130.72 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 146.3 GB | 188.9 GB | 145.66 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 150.0 GB | 192.6 GB | 149.39 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 179.9 GB | 222.5 GB | 179.27 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 213.5 GB | 256.1 GB | 212.89 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 247.1 GB | 289.8 GB | 246.50 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 299.4 GB | 342.0 GB | 298.79 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 Hy3?
Q4_K_M · 179.9 GBHy3 (Q4_K_M) requires 179.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 234+ GB is recommended. Using the full 262K context window can add up to 42.6 GB, bringing total usage to 222.5 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Hy3?
Q4_K_M · 179.9 GB6 devices with unified memory can run Hy3, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 256GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download Hy3
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 Hy3 need?
Hy3 requires 179.9 GB of VRAM at Q4_K_M, or 598.2 GB at BF16. Full 262K context adds up to 42.6 GB (222.5 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 298.8B × 4.8 bits ÷ 8 = 179.3 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 43.2 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M179.9 GBQ4_K_M + full context222.5 GB- Can NVIDIA GeForce RTX 5090 run Hy3?
No — Hy3 requires at least 82.8 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Hy3?
For Hy3, Q4_K_M (179.9 GB) offers the best balance of quality and VRAM usage. Q4_K_L (183.6 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 82.8 GB.
VRAM requirement by quantization
IQ2_XXS82.8 GBQ2_K127.6 GBQ3_K_L153.8 GBQ4_K_M ★179.9 GBQ4_K_L183.6 GBBF16598.2 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Hy3 on a Mac?
Hy3 requires at least 82.8 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 Hy3 locally?
Yes — Hy3 can run locally on consumer hardware. At Q4_K_M quantization it needs 179.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hy3?
At Q4_K_M, Hy3 can reach ~25 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 179.9 × 0.65 = ~29 tok/s
Estimated speed at Q4_K_M (179.9 GB)
~29 tok/s~29 tok/s~25 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Hy3?
At Q4_K_M, the download is about 179.27 GB. The full-precision BF16 version is 597.57 GB. The smallest option (IQ2_XXS) is 82.17 GB.
- Which GPUs can run Hy3?
No single consumer GPU has enough VRAM to run Hy3 at Q4_K_M (179.9 GB). Multi-GPU or professional hardware is required.
- Which devices can run Hy3?
6 devices with unified memory can run Hy3 at Q4_K_M (179.9 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), Mac Studio M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.