Chinese AI startup DeepSeek has begun developing its own AI chips focused on inference workloads to reduce reliance on NVIDIA and cut costs, sources told Reuters. The project is in early stages and ha…
Moonshot AI released Kimi K2.7 Code, a 1-trillion-parameter open-source coding model under a near-MIT license, but its 594GB size at 4-bit quantization makes local deployment impractical for most user…
Mixture-of-Experts (MoE) models like Qwen3-30B-A3B and DeepSeek-V3 separate total parameters (memory) from active parameters (compute), allowing a 30B-parameter model to run at the speed of a 3B model…
A developer outlines a cost-effective AI workflow combining open-source local models with paid APIs, achieving a monthly cost of $20-30 plus initial hardware. The approach uses DeepSeek-V3 via Ollama …
NVIDIA swept MLPerf Training v6.0 benchmarks, achieving the fastest training times at scale and highest per-accelerator performance across all tests, including new DeepSeek-V3 and GPT-OSS-20B workload…
NVIDIA's Blackwell platform swept MLPerf Training 6.0, achieving the fastest training times across all seven benchmarks, scaling to 8,192 GPUs on DeepSeek-V3 671B, and delivering up to 1.6x performanc…
A developer's guide to budget prompt engineering reveals that maximizing information density while minimizing token count can achieve premium-tier productivity from budget models like GPT-4.1-mini, De…
NVIDIA introduced advanced fused MLP kernels for mixture-of-experts (MoE) models, built with the CuTe DSL, delivering 1.3x–2x kernel-level speedups and enabling sync-free MoE execution. The optimizati…
Prahlad Yeri published a guide on prompt engineering for budget-tier AI models, targeting developers and students in cost-sensitive markets like Bangalore and Jakarta. The article teaches structured p…
Researchers have developed L-VARC, a novel framework that enhances visual reasoning on the Abstraction and Reasoning Corpus (ARC) by integrating a language-guided Learning Using Privileged Information…
Mixture-of-Experts (MoE) architecture allows large language models to use only a fraction of their total parameters for each token, enabling models with 671 billion total parameters to run at speeds c…
A developer built a cost-saving solution combining Qwen-Turbo and DeepSeek series APIs, cutting total token costs up to 72% without reducing response quality. The system uses task-based model routing,…
Researchers have developed ReasoningFlow, a framework that maps the non-linear discourse structures of large reasoning model (LRM) traces into directed acyclic graphs (DAGs) to improve evaluation and …
A developer discovered that standard quantization pipelines for large language models silently discard multi-token prediction (MTP) heads, causing speculative decoding speedups to vanish despite the b…
A developer built Micro-Expert-Router, a Rust inference engine that streams Mixture-of-Experts model weights directly from NVMe SSDs using io_uring with O_DIRECT, eliminating the need for GPU VRAM. Th…
Researchers at the FlashInfer MLSYS Challenge developed a formal verification method using the SPIN model checker to detect deadlocks in CuTe DSL kernels running on NVIDIA B200 GPUs. The approach, dem…
**Summary:** Multi-Head Latent Attention (MLA) is an attention mechanism used in DeepSeek-V2/V3 and Kimi K2.x models that compresses the Key-Value (KV) cache by projecting full KV pairs into a shared,…