The developers of Paddock, a Rust/C++ inference engine with its own CUDA kernels, released the code as open source on schedule, fulfilling an August commitment to ship in September. The public repo is their internal repo, including kernels, and the engine already serves roughly 300B tokens per year in production at their company. Practitioners get a single binary exposing OpenAI- and Anthropic-style APIs that loads GGUF and safetensors weights.
A developer team optimized AMD's software stack down to the kernel level for Qwen3.6-35B-A3B on MI350X GPUs, achieving 78,498 output tokens per second across 8 GPUs. The work aims to close the software gap with NVIDIA's CUDA ecosystem, leveraging MI350X's raw compute advantage over B200.
A developer team optimized AMD's software stack down to the kernel level for Qwen3.6-35B-A3B on MI350X GPUs, achieving 78,498 output tokens per second across 8 GPUs. The work aims to close the software gap with NVIDIA's CUDA ecosystem, leveraging MI350X's raw compute advantage over B200.
A developer released TensorSharp, a new open-source local LLM inference engine supporting Unsloth GGUF models, and published benchmarks showing on-par performance with llama.cpp on CUDA and Vulkan. The engine supports multi-modal models like Gemma4, Qwen3.6, and DiffusionGemma, and offers OpenAI/Ollama-compatible APIs.
A developer released TensorSharp, a new open-source local LLM inference engine supporting Unsloth GGUF models, and published benchmarks showing on-par performance with llama.cpp on CUDA and Vulkan. The engine supports multi-modal models like Gemma4, Qwen3.6, and DiffusionGemma, and offers OpenAI/Ollama-compatible APIs.
A developer released Reflex, a GGUF-native Rust/CUDA inference engine (MIT licensed) built for cold-start latency rather than steady-state throughput. It supports DeepSeek-V2/V3 Multi-head Latent Attention and Qwen3 family models, and benchmarks ~1.3-1.4x faster than llama.cpp cold-start on an A6000. It targets one-shot/serverless embedding, not server deployment.
A developer released Reflex, a GGUF-native Rust/CUDA inference engine (MIT licensed) built for cold-start latency rather than steady-state throughput. It supports DeepSeek-V2/V3 Multi-head Latent Attention and Qwen3 family models, and benchmarks ~1.3-1.4x faster than llama.cpp cold-start on an A6000. It targets one-shot/serverless embedding, not server deployment.
A from-scratch LLM inference engine written in Rust and CUDA, specifically tuned for the RTX 5090 Laptop GPU (Blackwell sm_120a). It supports NVFP4 quantization, mixture-of-experts (MoE), and multi-token prediction (MTP) speculative decoding, achieving up to 1.6x speedup over llama.cpp on target models. Designed for developers who need maximum inference performance on a single high-end laptop GPU.
A from-scratch LLM inference engine written in Rust and CUDA, specifically tuned for the RTX 5090 Laptop GPU (Blackwell sm_120a). It supports NVFP4 quantization, mixture-of-experts (MoE), and multi-token prediction (MTP) speculative decoding, achieving up to 1.6x speedup over llama.cpp on target models. Designed for developers who need maximum inference performance on a single high-end laptop GPU.
A developer released PicoLM v1.0-rc1, an LLM inference engine written in C99, on GitHub and announced it on Hacker News. It supports llama-2, GPT-2, Qwen 3.6/3.8 with MoE, and Gemma-3n models, with heavy emphasis on CPU SIMD acceleration and cross-platform portability. For practitioners, it offers a lightweight inference option spanning platforms from DOS to modern OSes.
A developer released PicoLM v1.0-rc1, an LLM inference engine written in C99, on GitHub and announced it on Hacker News. It supports llama-2, GPT-2, Qwen 3.6/3.8 with MoE, and Gemma-3n models, with heavy emphasis on CPU SIMD acceleration and cross-platform portability. For practitioners, it offers a lightweight inference option spanning platforms from DOS to modern OSes.