• Mac Platform Support: Full macOS compatibility with Metal GPU detection for Apple Silicon (M1/M2/M3) and Intel GPUs

• Multi-GPU Support: Select and profile multiple GPUs simultaneously with side-by-side performance comparison

• GPU Filter Dropdown: Filter profiling results by specific GPU

• Remote GPU Support: Full SSH connection to remote GPU servers with seamless CUDA environment integration

• Dynamic Profiling Methods: 5 profiling options (NCU Full, Fast, Static, Line-by-Line, Kernel Replay) with quick-switch buttons

• Simplified Chat Modes: Streamlined to Agent, Gather, and Forge only (Coming soon)

• Chart Rendering: Better performance visualization for profiling data

• Double Credit Consumption: Fixed bug charging credits twice

• Profiling Data Persistence: No more data loss on view refresh

• SSL Handshake Issues: Fixed connection stability

• Iterate Mode: Removed and consolidated into simplified chat mode system

• New GPU Emulator built from scratch with cycle-accurate scheduling and multi-warp latency simulation

• PTX and SASS translation for deep low-level analysis and debugging

• Remote connection support (SSH + WSL) to run and profile kernels anywhere

• Agentic AI "Iterate Mode" that writes, profiles, and optimizes kernels automatically until peak performance

• Kernel fusion detection for better performance across sequential and parallel operations (Beta Users)

• Enhanced benchmarking and profiling with full metric breakdowns and bottleneck detection

• Local LLMs now work perfectly

• 96-98% emulator accuracy vs real GPUs

• Simulation speed under 100ms for 1,000 instructions

• 30% more accuracy than previous builds

• Remote GPU connection via SSH integration

• Native support for GPU cloud providers (RunPod, Google Cloud, AWS, Azure, Paperspace, Vast.ai, Lambda Labs)

• Seamless profiling on remote GPUs as if they were local

• Automatic GPU detection on remote machines

• Smart Profiling Terminal with AI-powered insights

• Automatic bottleneck detection (memory-bound vs compute-bound)

• NCU-compatible metrics without requiring hardware

• AI-generated optimization suggestions (memory coalescing, bank conflicts, occupancy, branch divergence)

• Fixed NCU GUI integration for report generation

• Enhanced profiling UI with collapsible sections

• WebWorker-based analysis for non-blocking performance

• LRU caching for instant re-analysis

• Improved error handling and fallback mechanisms

• Full GPU emulator for profiling without physical hardware

• 86+ GPU architectures supported

• Static kernel analysis engine (under 100ms)

• Roofline model implementation with ±15% accuracy

• Architecture comparison across multiple GPUs instantly

• Benchmarking Terminal for benchmark sweeps and custom kernel configurations

• Visual comparison between kernels

• Static Profiling with instant CUDA kernel insights in CodeLens

• Real-time registers, shared memory, and occupancy analysis while typing

• Profile with Configs - complete cycle with persistent configs and history

• Tools Detector (nvidia-smi, nsight compute, nvcc)

• Execution time, memory bandwidth, occupancy, SM efficiency, and register usage metrics

• Data size presets, warmup runs, and execution controls

• Grid/block optimization with automatic suggestions

• Multi-GPU support with device-specific benchmarking

• Session management with persistence across restarts

• Sortable results with performance indicators

• CSV export for sharing benchmark results

• OpenAI, Anthropic, Deepseek integration

• Local Ollama and vLLM support

• BYOK (Bring Your Own Key) flexibility

• Fill-in-the-Middle autocomplete

• NVIDIA Nsight Compute integration

• Real-time GPU performance metrics

• Hardware detection and optimization

• CUDA syntax highlighting and IntelliSense