19:19
How to Build Things with Jev & OpenJevs
Sam Witteveen builds a working model router using Jev, a "system one" decision model from TypeSafe AI that returns typed, probability...
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14:30
MiniCPM5-2B: The Best Sub-Agent Model Yet?
Sam Witteveen examines MiniCPM 2B (technically 2.5B), the latest small model from OpenBMB, which claims to beat 4B-class models on fu...
12:29
Nex-N2.5 Mini: Multilingual, Multimodal, and Fully Agentic (Hands-On)
Fahd Mirza provides a hands-on deployment walkthrough and capability test of Nex AGI's N2.5 Mini, the smaller model in the N2.5 agent...
01:28:12
Deep dive on LLM Inference at Scale — Harshul Jain, Audible & Tanmay Sah, Independent AI Researcher
Harshul Jain, senior software engineer at Audible and author of an open-source LLM inference handbook, teams up with AI researcher Ta...
13:50
MiniCPM5 2B: SOTA or Scam? Let’s Test Locally
Fahd Mirza puts MiniCPM5 2B — the latest small model from ModelBench and Tsinghua University's NLP lab — through a gauntlet of real-w...
11:30
Spark X2.5 4B: What a 4B Model Can and Can’t Do Locally
Fahd Mirza puts the newly released Spark X2.5 4B through a full local deployment and capability evaluation on a 48GB VRAM GPU. The mo...
12:54
Qwen3.8-27B in 2-Bit Quant: Escha-W2 Build Locally without Loss
Fahd Mirza demonstrates Escha-W2, Asha Labs' aggressively quantized version of Qwen3.8 27B, which compresses the model from 50GB at f...
09:20
DFlash 2: Qwen3.8-27B at 2× Speed – Live Benchmark Locally
Fahd Mirza benchmarks DFlash 2, a community-developed speculative decoding enhancement for the Qwen3.8-27B model, running live on an...
08:39
Why You Shouldn’t Run Qwen3.8 2.4T Locally
Fahd Mirza delivers a frank assessment of Qwen's newly released Qwen3 2.4-trillion-parameter open-weight model, making the case that...
19:50
Taking Reinforcement Learning Cross Datacenter — Nan Jiang, Modal
At an AI Engineer conference, Nan Jiang from Modal presents a technical architecture for running reinforcement learning post-training...