PhantomGPU: GPU performance emulator to benchmark ML models on virtual GPUs

4 hours ago 3

Test ML models on any GPU before you buy it

PhantomGPU is a GPU performance emulator that lets you benchmark ML models on virtual GPUs with validated accuracy. Compare performance across different GPUs and estimate costs without access to physical hardware.

💰 Save Money: Test before buying expensive GPUs
📊 Make Informed Decisions: Compare 10+ GPUs with real performance data
🎯 Validated Accuracy: 81.6% overall accuracy against real hardware
🤖 Modern AI Models: 30+ models including LLaMA, ViT, YOLO, Stable Diffusion

# Clone and build git clone https://github.com/bugthesystem/phantom-gpu.git cd phantom-gpu cargo build --release --features real-models # See available GPUs ./target/release/phantom-gpu list-gpus # Test a model on different GPUs ./target/release/phantom-gpu compare-models \ --models "llama2-7b" \ --gpus "v100,a100,rtx4090" \ --batch-sizes "1,8" # Validate accuracy against real hardware ./target/release/phantom-gpu validate

✅ Tesla V100: 76.1% accuracy (±23.9% error) - Fair
✅ A100: 84.5% accuracy (±15.5% error) - Good
✅ RTX 4090: 84.1% accuracy (±15.9% error) - Good
📊 Overall: 81.6% accuracy

Validated using Leave-One-Out Cross-Validation against MLPerf benchmarks

GPU Memory Architecture Status

H200	141GB	Hopper	In Development
H100	80GB	Hopper	In Development
RTX 5090	32GB	Blackwell	In Development
RTX 4090	24GB	Ada Lovelace	✅ 84.1% Accuracy
A100	80GB	Ampere	✅ 84.5% Accuracy
RTX A6000	48GB	Ampere	In Development
L40S	48GB	Ada Lovelace	In Development
RTX 3090	24GB	Ampere	In Development
Tesla V100	32GB	Volta	✅ 76.1% Accuracy

30+ cutting-edge AI models across all major categories:

GPT-3.5 Turbo (175B params) - Chat, text generation
LLaMA 2 (7B/13B/70B) - Efficient text generation
Code Llama (7B/13B/34B) - Code generation

ViT-Base/16, ViT-Large/16 - Image classification
CLIP ViT-B/16, CLIP ViT-L/14 - Vision-language tasks
DeiT-Base, DeiT-Large - Efficient transformers

YOLOv8/v9/v10 - Real-time detection
DETR, RT-DETR - Transformer-based detection

Stable Diffusion, Stable Diffusion XL - Text-to-image generation

ResNet-50, BERT-Base, GPT-2 - For compatibility

Compare LLaMA 2 7B Performance

$ ./target/release/phantom-gpu compare-models \ --models "llama2-7b" \ --gpus "v100,a100,rtx4090" \ --batch-sizes "1,8" 🏆 Model Performance Comparison Model GPU Batch Time (ms) Throughput Memory (MB) -------------------------------------------------------------------------- llama2-7b Tesla V100 1 45.2 22.1 14800 llama2-7b Tesla V100 8 28.6 279.7 28400 llama2-7b A100 1 18.9 52.9 15200 llama2-7b A100 8 12.4 645.2 30800 llama2-7b RTX 4090 1 21.5 46.5 14600 llama2-7b RTX 4090 8 14.8 540.5 29200 📈 Summary 🏆 Best Performance: A100 (645.2 samples/sec at batch=8) 💰 Best Value: RTX 4090 (540.5 samples/sec, consumer price)

$ ./target/release/phantom-gpu validate 🎯 PhantomGPU Accuracy Validation ================================================== GPU Validation Results: ✅ Tesla V100: 76.1% accuracy (±23.9% error) - Fair ✅ A100: 84.5% accuracy (±15.5% error) - Good ✅ RTX 4090: 84.1% accuracy (±15.9% error) - Good 📊 Overall System: 81.6% accuracy (±18.4% error) 🎯 Status: Validated against real hardware benchmarks

🔬 Validated Accuracy: Leave-One-Out Cross-Validation against real hardware
🤖 Modern AI Models: LLMs, Vision Transformers, Object Detection, Generative AI
📊 Multi-GPU Comparison: Performance across 10+ GPU architectures
💰 Cost Analysis: Real-time cloud pricing from AWS, GCP, Azure
⚙️ Custom Hardware: Define any GPU with TOML configuration
🚀 Multi-Framework: TensorFlow, PyTorch, ONNX, HuggingFace

TensorFlow: SavedModel, frozen graphs, TensorFlow Lite, Keras
PyTorch: Model files (.pth, .pt)
ONNX: Standard ONNX models (.onnx)
Candle Minimalist ML framework for Rust
HuggingFace: Direct loading from HuggingFace Hub

# Install Rust curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh source ~/.cargo/env

git clone https://github.com/bugthesystem/phantom-gpu.git cd phantom-gpu cargo build --release --features real-models

# See all available commands ./target/release/phantom-gpu --help # List GPUs ./target/release/phantom-gpu list-gpus # Test specific model ./target/release/phantom-gpu benchmark --model llama2-7b --batch-size 8 # Compare models ./target/release/phantom-gpu compare-models \ --models "llama2-7b,vit-base-16" \ --gpus "v100,a100,rtx4090" \ --batch-sizes "1,8" # Validate accuracy ./target/release/phantom-gpu validate --verbose

PhantomGPU uses TOML files for configuration: