Top 7 Coding Models You Can Run Locally in 2026

Building AI systems at scale is demanding, requiring low-latency inference, fast vector search, strong GPU price-performance and infrastructure that can grow without multiplying operational complexity.  NVIDIA’s latest work with Amazon Web Services (AWS) addresses each of those constraints. Across Amazon OpenSearch and Amazon EC2, NVIDIA AI infrastructure is giving enterprises more practical paths to deploy […]

In this tutorial, we build a multilingual ASR and speech translation pipeline with NVIDIA Canary-1B-v2. We load the model on a GPU-enabled runtime, prepare audio into 16 kHz mono, and run English ASR. We then translate speech into French, German, Spanish, and Italian, and extract word and segment timestamps. We export translated subtitles as an SRT file, test long-form transcription, run batch processing, and benchmark inference speed. The post How to Use NVIDIA Canary-1B-v2 for ASR, Translation, and Automatic SRT Subtitle Export in Python appeared first on MarkTechPost.

SpaceX's deal with Reflection AI highlights the growing demand for large-scale GPU access, setting a new cost benchmark in the compute market. The post SpaceX signs $6.3B computing power deal with AI startup Reflection appeared first on Crypto Briefing.

The PCIe transfer latency is silently bottlenecking your agentic inference. Here is how building a custom device-resident vector search kernel bypasses the CPU to unlock deterministic microsecond tail latencies. The post GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step Would Stop Bouncing Off the GPU appeared first on Towards Data Science.

HIVE shares rose after BUZZ HPC signed a $220M AI cloud deal with Bell and Cohere, adding sovereign GPU capacity in Canada.

BTTInferGrid is a decentralized GPU computing network purpose-built for AI inference. By bridging the global supply of idle GPU capacity with the surging demand for AI workloads, BTTInferGrid delivers an open-access, verifiably secure, and pay-as-you-go computing infrastructure for AI developers worldwide.   On June 17, BitTorrent, a pioneer in decentralized technology,

Fortinet's Nvidia partnership strengthens AI security, potentially setting new standards for safeguarding AI workloads in cloud environments. The post Fortinet partners with Nvidia to enhance GPU-powered AI security appeared first on Crypto Briefing.

We implement xFormers, a practical toolkit for fast, memory-efficient Transformer models on GPUs. We validate memory-efficient attention against a standard implementation, then compare speed and memory across sequence lengths. We work through causal masking, packed variable-length sequences, grouped-query attention, and custom ALiBi biases. Finally, we combine these into a trainable GPT-style model with SwiGLU layers and automatic mixed-precision training. The post How to Build Memory-Efficient Transformers with xFormers Using Packed Sequences, GQA, ALiBi, SwiGLU, and Causal Attention appeared first on MarkTechPost.