Moonshot AI’s Kimi K3 is the first open-source model to reach 2.8 trillion parameters, a scale that, until now, has been the exclusive territory of closed, proprietary systems. Built for long-horizon coding, agentic knowledge work, and multimodal reasoning, it activates 104 billion of those parameters per token through a sparse Mixture-of-Experts architecture, keeping inference tractable […]

When an AI system yields unreliable answers, the root cause could be an unclear system prompt, missing context, poor retrieval quality, or simply using the wrong base model. Teams end up spending weeks experimenting with prompt changes, retrieval-augmented generation (RAG), or fine-tuning to improve response quality. But before deciding which technique to adopt, it is […]

Open-source multimodal models have a benchmark problem. Every new release comes with DocVQA and MMMU scores, but those numbers rarely reflect how a model performs on a real workload. A model can lead the leaderboard and still struggle with a scanned invoice, a noisy image, or a multi-step agent workflow. Real-world data is far less […]

Somebody on your team read a benchmark post, and now there’s a ticket to migrate the inference stack. That’s how most vLLM vs SGLang decisions start. A published test reports a 29 percent throughput gap, the number lands in Slack, and two weeks later you’re debugging kernel version conflicts at midnight while p99 latency sits […]