Featherless

NeevCloud is a full-stack AI SuperCloud for building, training, fine-tuning, and deploying AI models at scale. Access GPU AI Services powered by NVIDIA H100, B200, and GB200 NVL72; a pay-per-token Model API supporting Llama 3, Mixtral, Qwen, and Stable Diffusion; and Agentic Studio for building, testing, and shipping AI agents with built-in governance and observability. The platform is Kubernetes-native, OpenAI-compatible, and designed for zero lock-in with no egress fees and transparent pricing. Cloud Servers, Snapshots, Load Balancers, and Orchestration round out the IaaS layer. S3-compatible object storage is available through Zata.ai. NeevCloud owns every infrastructure layer, from GPU clusters to AI orchestration software, delivering strong price-to-performance, data sovereignty, and instant GPU access with no waiting lists. Built for AI startups, ML engineers, data scientists, enterprises, and research institutions scaling AI workloads.

oMLX is a macOS-native MLX server designed to make local AI faster and more practical on Apple Silicon. Built for the way coding agents actually work, it uses paged SSD KV caching to persist cache blocks to disk, allowing previously seen prefixes to be restored across requests and server restarts instead of being recomputed from scratch. This can reduce time to first token on long contexts from 30–90 seconds to under five seconds after the first turn. Continuous batching handles concurrent requests through mlx-lm’s BatchGenerator, improving generation throughput without forcing requests to wait behind a single job. oMLX can serve LLMs, vision-language models, embedding models, and rerankers simultaneously, using LRU eviction when memory runs low. It supports any MLX-format model from Hugging Face, including Qwen, LLaMA, Mistral, Gemma, DeepSeek, MiniMax, and GLM, and can reuse models already stored in the standard Hugging Face cache, LM Studio folders, or custom directories.