Hy3 REAP 200B 21B — Hardware Requirements & GPU Compatibility
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Hy3 REAP 200B 21B is a 199.6B-parameter open language model from OpenMOSE in the Hunyuan 3 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 120.39 GB of VRAM — see which GPUs and Macs can run it below.
247 downloads
2 likesSpecifications
- Publisher
- OpenMOSE
- Family
- Hunyuan 3
- Parameters
- 199.6B
- Architecture
- HYV3ForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 120,832
- Release Date
- 2026-07-16
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Hy3 REAP 200B 21B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| IQ2_M | 2.70 | 68 GB | 110.6 GB | 67.36 GB | Importance-weighted 2-bit, medium |
| IQ3_XXS | 3.10 | 78.0 GB | 120.6 GB | 77.34 GB | Importance-weighted 3-bit |
| Q2_Kest. | 3.40 | 85.5 GB | 128.1 GB | 84.82 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 97.9 GB | 140.6 GB | 97.30 GB | 3-bit medium quantization |
| IQ4_XS | 4.30 | 107.9 GB | 150.5 GB | 107.28 GB | Importance-weighted 4-bit, compact |
| Q4_K_M | 4.80 | 120.4 GB | 163 GB | 119.75 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 142.8 GB | 185.4 GB | 142.20 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 165.3 GB | 207.9 GB | 164.66 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 200.2 GB | 242.8 GB | 199.58 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 399.8 GB | 442.4 GB | 399.17 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 REAP 200B 21B?
Q4_K_M · 120.4 GBHy3 REAP 200B 21B (Q4_K_M) requires 120.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 157+ GB is recommended. Using the full 262K context window can add up to 42.6 GB, bringing total usage to 163 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Hy3 REAP 200B 21B?
Q4_K_M · 120.4 GB8 devices with unified memory can run Hy3 REAP 200B 21B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Pro 16" M5 Max (128 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download Hy3 REAP 200B 21B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Frequently Asked Questions
- How much VRAM does Hy3 REAP 200B 21B need?
Hy3 REAP 200B 21B requires 120.4 GB of VRAM at Q4_K_M, or 399.8 GB at BF16. Full 262K context adds up to 42.6 GB (163 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 199.6B × 4.8 bits ÷ 8 = 119.8 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_M120.4 GBQ4_K_M + full context163.0 GB- Can NVIDIA GeForce RTX 5090 run Hy3 REAP 200B 21B?
No — Hy3 REAP 200B 21B requires at least 68 GB at IQ2_M, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Hy3 REAP 200B 21B?
For Hy3 REAP 200B 21B, Q4_K_M (120.4 GB) offers the best balance of quality and VRAM usage. Q5_K_M (142.8 GB) provides better quality if you have the VRAM. The smallest option is IQ2_M at 68 GB.
VRAM requirement by quantization
IQ2_M68.0 GBQ2_K85.5 GBQ4_K_M ★120.4 GBQ5_K_M142.8 GBQ6_K165.3 GBBF16399.8 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Hy3 REAP 200B 21B on a Mac?
Hy3 REAP 200B 21B requires at least 68 GB at IQ2_M, 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 REAP 200B 21B locally?
Yes — Hy3 REAP 200B 21B can run locally on consumer hardware. At Q4_K_M quantization it needs 120.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Hy3 REAP 200B 21B?
At Q4_K_M, Hy3 REAP 200B 21B can reach ~37 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 ÷ 120.4 × 0.65 = ~43 tok/s
Estimated speed at Q4_K_M (120.4 GB)
~43 tok/s~43 tok/s~37 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Hy3 REAP 200B 21B?
At Q4_K_M, the download is about 119.75 GB. The full-precision BF16 version is 399.17 GB. The smallest option (IQ2_M) is 67.36 GB.
- Which GPUs can run Hy3 REAP 200B 21B?
No single consumer GPU has enough VRAM to run Hy3 REAP 200B 21B at Q4_K_M (120.4 GB). Multi-GPU or professional hardware is required.
- Which devices can run Hy3 REAP 200B 21B?
18 devices with unified memory can run Hy3 REAP 200B 21B at Q4_K_M (120.4 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.