Hy3 REAM 100B — Hardware Requirements & GPU Compatibility
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Hy3 REAM 100B is a 104.1B-parameter open language model from Akicou in the Hunyuan 3 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 63.12 GB of VRAM — see which GPUs and Macs can run it below.
261 downloads
3 likesSpecifications
- Publisher
- Akicou
- Family
- Hunyuan 3
- Parameters
- 104.1B
- Architecture
- HYV3ForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 120,832
- Release Date
- 2026-07-13
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HuggingFace
How Much VRAM Does Hy3 REAM 100B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 44.9 GB | 87.5 GB | 44.26 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 51.4 GB | 94.0 GB | 50.77 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 63.1 GB | 105.7 GB | 62.48 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 74.8 GB | 117.5 GB | 74.20 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 86.5 GB | 129.2 GB | 85.91 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 104.8 GB | 147.4 GB | 104.13 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 208.9 GB | 251.5 GB | 208.27 GB | Brain floating point 16 — preferred for training |
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 REAM 100B?
Q4_K_M · 63.1 GBHy3 REAM 100B (Q4_K_M) requires 63.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 83+ GB is recommended. Using the full 262K context window can add up to 42.6 GB, bringing total usage to 105.7 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Hy3 REAM 100B?
Q4_K_M · 63.1 GB22 devices with unified memory can run Hy3 REAM 100B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 96GB).
Runs great
— Plenty of headroom
Frequently Asked Questions
- How much VRAM does Hy3 REAM 100B need?
Hy3 REAM 100B requires 63.1 GB of VRAM at Q4_K_M, or 208.9 GB at BF16. Full 262K context adds up to 42.6 GB (105.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 104.1B × 4.8 bits ÷ 8 = 62.5 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_M63.1 GBQ4_K_M + full context105.7 GB- Can NVIDIA GeForce RTX 5090 run Hy3 REAM 100B?
No — Hy3 REAM 100B requires at least 44.9 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Hy3 REAM 100B?
For Hy3 REAM 100B, Q4_K_M (63.1 GB) offers the best balance of quality and VRAM usage. Q5_K_M (74.8 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 44.9 GB.
VRAM requirement by quantization
Q2_K44.9 GBQ4_K_M ★63.1 GBQ5_K_M74.8 GBQ6_K86.5 GBQ8_0104.8 GBBF16208.9 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Hy3 REAM 100B on a Mac?
Hy3 REAM 100B requires at least 44.9 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 Hy3 REAM 100B locally?
Yes — Hy3 REAM 100B can run locally on consumer hardware. At Q4_K_M quantization it needs 63.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hy3 REAM 100B?
At Q4_K_M, Hy3 REAM 100B can reach ~70 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 ÷ 63.1 × 0.65 = ~82 tok/s
Estimated speed at Q4_K_M (63.1 GB)
~82 tok/s~82 tok/s~70 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Hy3 REAM 100B?
At Q4_K_M, the download is about 62.48 GB. The full-precision BF16 version is 208.27 GB. The smallest option (Q2_K) is 44.26 GB.
- Which GPUs can run Hy3 REAM 100B?
No single consumer GPU has enough VRAM to run Hy3 REAM 100B at Q4_K_M (63.1 GB). Multi-GPU or professional hardware is required.
- Which devices can run Hy3 REAM 100B?
23 devices with unified memory can run Hy3 REAM 100B at Q4_K_M (63.1 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.