OUI 1 — Hardware Requirements & GPU Compatibility
ChatVision
OUI 1 is a 25.8B-parameter open language model from thesysdev. It supports a context window of up to 262,144 tokens. At BF16 it needs about 52.29 GB of VRAM — see which GPUs and Macs can run it below.
2.9K downloads
131 likesSpecifications
- Publisher
- thesysdev
- Parameters
- 25.8B
- Architecture
- DiffusionGemmaForBlockDiffusion
- Context Length
- 262,144 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-09-07
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does OUI 1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 52.3 GB | 96.2 GB | 51.65 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 OUI 1?
BF16 · 52.3 GBOUI 1 (BF16) requires 52.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 68+ GB is recommended. Using the full 262K context window can add up to 43.9 GB, bringing total usage to 96.2 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run OUI 1?
BF16 · 52.3 GB22 devices with unified memory can run OUI 1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 96GB).
Runs great
— Plenty of headroom
Related Models
Frequently Asked Questions
- How much VRAM does OUI 1 need?
OUI 1 requires 52.3 GB of VRAM at BF16. Full 262K context adds up to 43.9 GB (96.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 25.8B × 16 bits ÷ 8 = 51.6 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 44.6 GB (at full 262K context)
VRAM usage by quantization
BF1652.3 GBBF16 + full context96.2 GB- Can NVIDIA GeForce RTX 5090 run OUI 1?
No — OUI 1 requires at least 52.3 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run OUI 1 on a Mac?
OUI 1 requires at least 52.3 GB at BF16, 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 OUI 1 locally?
Yes — OUI 1 can run locally on consumer hardware. At BF16 quantization it needs 52.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is OUI 1?
At BF16, OUI 1 can reach ~92 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 ÷ 52.3 × 0.65 = ~99 tok/s
Estimated speed at BF16 (52.3 GB)
~99 tok/s~99 tok/s~92 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of OUI 1?
At BF16, the download is about 51.65 GB.
- Which GPUs can run OUI 1?
No single consumer GPU has enough VRAM to run OUI 1 at BF16 (52.3 GB). Multi-GPU or professional hardware is required.
- Which devices can run OUI 1?
23 devices with unified memory can run OUI 1 at BF16 (52.3 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.