Litespark-Nemotron-3.5 Super VL: Frontier CUDA Kernel Generation from PyTorch Code
An open-weights model based on NVIDIA Nemotron 3.5 Super VL to translate PyTorch modules into raw CUDA without the reliance on vendor libraries.
Accelerating AI Training Insights
Explore the latest research and breakthroughs in LLM pre-training, energy-efficient AI, and scalable generative models from the Mindbeam research team.
Research - Insights
Posts in Insights
Serving Nemotron 3.5 Super VL 120B-A12B on Litespark Inference
Litespark Inference serves NVIDIA’s Nemotron 3.5 Super VL on two H200 GPUs, reaching 962 tokens per second per user in warm-start benchmarks.
RL-GQE: Reinforcement Learning towards Generative Quantum Eigensolving
Application of Group Relative Policy Optimization and Self-Imitation Learning enable an autoregressive transformer to construct quantum circuits from scratch.
Discovery of Safer Novel Pain Therapeutics with Generative AI
Mindbeam uses generative AI to design novel TRPV1 modulators that mimic AM404 while aiming to avoid acetaminophen-related liver toxicity.
Ultra-Fast Ternary LLM Inference on CPUs with Litespark
How ternary weights, SIMD dot-product kernels, and Litespark-Inference make billion-parameter language models practical on Apple Silicon, Intel and AMD.
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