Uyu 2 28B — Hardware Requirements & GPU Compatibility
ChatRoleplay
Uyu 2 28B is a 28.2B-parameter open language model from mente-ai. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 18.53 GB of VRAM — see which GPUs and Macs can run it below.
2.7K downloads
21 likesSpecifications
- Publisher
- mente-ai
- Parameters
- 28.2B
- Architecture
- Uyu2ForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-07-10
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Uyu 2 28B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 13.6 GB | 181.4 GB | 11.98 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 15.4 GB | 183.2 GB | 13.74 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 18.5 GB | 186.3 GB | 16.91 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 21.7 GB | 189.5 GB | 20.08 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 24.9 GB | 192.7 GB | 23.25 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 29.8 GB | 197.6 GB | 28.18 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 58.0 GB | 225.8 GB | 56.36 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 Uyu 2 28B?
Q4_K_M · 18.5 GBUyu 2 28B (Q4_K_M) requires 18.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 25+ GB is recommended. Using the full 262K context window can add up to 167.8 GB, bringing total usage to 186.3 GB. 8 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Uyu 2 28B?
Q4_K_M · 18.5 GB41 devices with unified memory can run Uyu 2 28B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightWhere to Download Uyu 2 28B
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 Uyu 2 28B need?
Uyu 2 28B requires 18.5 GB of VRAM at Q4_K_M, or 58.0 GB at BF16. Full 262K context adds up to 167.8 GB (186.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 28.2B × 4.8 bits ÷ 8 = 16.9 GB
KV Cache + Overhead ≈ 1.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 169.4 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M18.5 GBQ4_K_M + full context186.3 GB- Can NVIDIA GeForce RTX 4090 run Uyu 2 28B?
Yes, at Q5_K_M (21.7 GB) or lower. Higher quantizations like Q6_K (24.9 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Uyu 2 28B?
For Uyu 2 28B, Q4_K_M (18.5 GB) offers the best balance of quality and VRAM usage. Q5_K_M (21.7 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 13.6 GB.
VRAM requirement by quantization
Q2_K13.6 GBQ4_K_M ★18.5 GBQ5_K_M21.7 GBQ6_K24.9 GBQ8_029.8 GBBF1658.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Uyu 2 28B on a Mac?
Uyu 2 28B requires at least 13.6 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 Uyu 2 28B locally?
Yes — Uyu 2 28B can run locally on consumer hardware. At Q4_K_M quantization it needs 18.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Uyu 2 28B?
At Q4_K_M, Uyu 2 28B can reach ~238 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~35 tok/s. 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 ÷ 18.5 × 0.65 = ~281 tok/s
Estimated speed at Q4_K_M (18.5 GB)
~281 tok/s~35 tok/s~281 tok/s~238 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Uyu 2 28B?
At Q4_K_M, the download is about 16.91 GB. The full-precision BF16 version is 56.36 GB. The smallest option (Q2_K) is 11.98 GB.
- Which GPUs can run Uyu 2 28B?
8 consumer GPUs can run Uyu 2 28B at Q4_K_M (18.5 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Uyu 2 28B?
41 devices with unified memory can run Uyu 2 28B at Q4_K_M (18.5 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (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.