16.2B Flow-MMDiT Foundation Architecture • 100% On-Device Privacy

The 16-Billion Manifold,
Native on Personal Hardware.

Photorealistic generative intelligence running natively on your workstation. Zero cloud latency. Zero monthly GPU rental tolls. Synthesized with extreme acutance across Apple Silicon, Windows CUDA, and Linux.

Foundation Architecture
16.2 Billion
Flow-MMDiT Weights
Apple Silicon Support
M1 – M4 Ready
Runs on M2 MacBook Air (8GB)
Data Sovereignty
0 Bytes Sent
100% Private Offline Generation
Cross-Platform Engine
Metal 3 • CUDA
macOS, Windows & Linux
• Verified FxPlor 16B Output • Zero-Gravity Physics • 1024×1024
Astronaut floating inside space station module generated by FxPlor 16B
"Astronaut floating in micro-gravity space module, floating water spheres with reflections, complex electrical wiring and instrumentation" Verified FxPlor 16B
Universal Architecture

Recommended Hardware Specifications

FxPlor 16B is engineered with adaptable quantization kernels. Review the empirical system requirements across Apple Silicon, Windows, and Linux workstations.

macOS (Apple Silicon)

Metal 3 • ANE
Entry / Baseline

Apple M1 / M2 MacBook Air (8GB RAM)
Uses INT4 quantized caching with unified memory swap.

⏱ Approx. ~3 Minutes per 1024×1024 Image
Recommended

Apple M2 / M3 / M4 Pro (16GB – 36GB RAM)
Active cooling with dedicated 16-core Neural Engine.

⏱ Approx. 25 – 45 Seconds per Image
Studio Pro

Apple M2 / M3 Ultra or M4 Max (48GB – 128GB)
Full FP16 uncompressed tensors with 400 GB/s bandwidth.

⏱ Approx. 12 – 18 Seconds per Image
OS: macOS Sonoma 14.0+ or macOS Sequoia 15.0+ • Minimum 20 GB SSD storage.
⊞

Windows (CUDA / DirectML)

NVIDIA • DirectX
Minimum

NVIDIA RTX 3060 (12GB VRAM)
16 GB System RAM, CUDA 12.x or DirectML backend.

⏱ Approx. 40 – 60 Seconds per Image
Recommended

NVIDIA RTX 4070 Ti / 4080 (16GB VRAM)
32 GB System RAM, TensorRT acceleration.

⏱ Approx. 10 – 16 Seconds per Image
Studio Pro

NVIDIA RTX 4090 (24GB VRAM) / RTX 6000 Ada
64 GB System RAM, FP16 FlashAttention-2.

⏱ Approx. 4 – 8 Seconds per Image
OS: Windows 11 64-bit • NVIDIA Studio / Game Ready Driver 550+ • 25 GB NVMe SSD.
>_

Linux / Cloud Servers

CUDA • ROCm
Minimum

NVIDIA RTX 3080 / 4070 (12GB VRAM)
16 GB RAM, PyTorch 2.4+ with cuDNN 9.x.

⏱ Approx. 30 – 45 Seconds per Image
Recommended

NVIDIA A10G / L4 / RTX 4080 (24GB VRAM)
32 GB RAM, vLLM / TensorRT-LLM pipeline.

⏱ Approx. 8 – 14 Seconds per Image
Cluster / Enterprise

NVIDIA H100 / A100 (80GB) or AMD MI300X
High-throughput parallel multi-client batching.

⏱ Sub-Second Batched Throughput
Distros: Ubuntu 22.04 / 24.04 LTS, Arch Linux, RHEL 9 • Docker / OCI container ready.
Transparent Ground Truth

Real-World Generation Benchmarks

We believe in honest, empirical performance data. Here is exactly how FxPlor 16B performs across real consumer laptops and workstation rigs.

Hardware System RAM / VRAM 1024×1024 Runtime Power Draw Data Privacy
Apple M2 MacBook Air (Passive Cooling) 8 GB Unified RAM ~3 Minutes (180s) 14 Watts (Cold & Silent) 100% Offline On-Device
Apple M3 / M4 Pro (Active Fan Cooling) 18 GB – 36 GB Unified ~25 – 45 Seconds 28 Watts 100% Offline On-Device
Apple M2 / M3 Max / Ultra Workstation 48 GB – 128 GB Unified ~14 – 20 Seconds 45 Watts 100% Offline On-Device
Desktop Workstation (NVIDIA RTX 4090) 24 GB GDDR6X ~4 – 8 Seconds 450 Watts 100% Offline On-Device
Traditional Cloud APIs (Midjourney / Flux) Cloud H100 Clusters 15s – 35s Queue Wait Mega-Watt Server Farms Prompts Logged on Cloud

FxPlor AI Studio available soon

Developer & Creator Preview

Join the FxPlor Early Access

Be the first to receive download links when the public demo builds for macOS and Windows go live on fxplorai.in.

Please enter a valid email address.

Zero spam. Notifications sent exclusively upon macOS & Windows demo releases on fxplorai.in.

You're on the FxPlor Demo Waitlist!

We have reserved your invitation. When the signed DMG and installer packages are compiled for distribution, you will receive your early download link.