Java framework compiles directly to CUDA for GPU LLM inference

A new Java framework called jitLLM has been developed that compiles Java bytecode directly into CUDA, enabling LLM inference on NVIDIA GPUs without requiring Python or C++ sidecars. Developed by the TornadoVM team at the University of Manchester with collaboration from Red Hat, jitLLM claims to achieve approximately 90% of the performance of llama.cpp. The framework supports various models including Llama 3, Mistral, and Qwen, and uses TornadoVM's JIT compiler to translate Java methods into GPU kernels at runtime, potentially simplifying the integration of AI inference into existing Java applications. AI

IMPACT Potentially simplifies LLM integration for Java developers by eliminating Python/C++ dependencies.

RANK_REASON New framework described in a dev.to post that compiles Java to CUDA for LLM inference, with claims of high performance. [lever_c_demoted from research: ic=1 ai=0.7]

Read on dev.to — LLM tag →

• CUDA
• Devstral 2
• IBM Granite
• Java
• jitLLM
• Llama 3
• llama.cpp
• Nvidia
• Phi 3
• Qwen 2.5
• Qwen 3
• Red Hat
• TornadoVM
• University of Manchester

• infra
• product

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →