Deepseek has released DeepEP V2 and TileKernels.
Summary
Deepseek open-sourced DeepEP V2 and TileKernels, new GPU kernel libraries aimed at accelerating AI workloads.
Similar Articles
deepseek-ai/DeepGEMM
DeepSeek releases DeepGEMM, a high-performance CUDA kernel library for LLM computation primitives including FP8/FP4/BF16 GEMMs, fused MoE with overlapped communication, and MQA scoring, compiled at runtime via JIT with no installation-time CUDA compilation required. The library achieves up to 1550 TFLOPS on H800 and matches or exceeds expert-tuned libraries across various matrix shapes.
deepseek-ai/DeepSeek-V4-Pro-DSpark
DeepSeek releases preview versions of its V4 series, including DeepSeek-V4-Pro (1.6T parameters, 49B activated) and DeepSeek-V4-Flash (284B parameters, 13B activated), both supporting a one-million-token context and featuring hybrid attention, manifold-constrained hyper-connections, and a Muon optimizer.
DeepSeek R2 just went open-source and it's matching GPT-4o on 9 of 12 benchmarks — for literally $0 in API costs
DeepSeek R2, a new open-source model, matches GPT-4o on nine of twelve benchmarks while running locally on a single A100 for zero API cost, potentially transforming the economics of AI deployment.
Deepseek drops another HUGE breakthrough - DSpark. Waaay faster than MTP [Video explaining it]
Deepseek announced DSpark, a new AI breakthrough that is significantly faster than MTP, as explained in a video.
Running DeepSeek-V4 locally with 4x legacy RTX 2080 Ti ($2k budget setup). Custom Turing kernels, W8A8 quantization, and 255 prefill tok/s!
A developer successfully runs DeepSeek-V4-Flash (284B total, 13B active) locally on four RTX 2080 Ti GPUs with a $2,500 budget, achieving 255 prefill tokens/s using custom Turing CUDA kernels, W8A8 quantization, and heterogeneous inference. The implementation is open-sourced.