Did FP8 make the model dumber? A per-prompt regression check for quantized serving
FP8 quantization boosted serving throughput for Qwen3-8B on an RTX PRO 6000 Blackwell GPU from 1,725 to 2,597 tokens per second at concurrency 32 using vLLM, achieving
→ View original sourceAgriciDaniel /claude-obsidian
Claude-obsidian is an open-source personal knowledge management tool that integrates Claude Code with Obsidian to create a self-organizing AI second brain. It automatically processes sources into a connected knowledge gr…
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[Benchmarks] Qwen3.8-27B on one DGX Spark across SGLang, vLLM and llama.cpp
I ran a 12-way Qwen3.8-27B comparison on one DGX Spark. Each engine used plain decoding plus MTP, DSpark, and DFlash2. The coding workload was a seeded 50-task HumanEval+ slice with
→ View original source[Release] Turing Engine: Serve LLaMA-3.1-70B, Qwen-2.5-72B & DeepSeek on a Single 24GB GPU (3,064 tok/s, 75% KV Compression, Unsloth Checkpoint Support)
Turing Engine is an open‑source framework that lets 70B–120B frontier models such as LLaMA‑3.1‑70B, Qwen‑2.5‑72B, and DeepSeek run on a single 24 GB consumer GPU (e.g., RTX 3090/4090, NVIDIA L4) with 75% KV‑cache compres…
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Inside LinkedIn's cognitive memory agent for agentic personalization
Ryan is joined by Praveen Bodigutla, Principal AI Researcher at LinkedIn, to chat about the four-layer memory system his team built to give LinkedIn's hiring assistant a persistent, personalized
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Prompt Engineering Certification: Build Practical AI Skills for the Future
<img alt=" " height="533" src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2
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YAML → MCP tools for vector databases
VectorSmith is an open-source Python library that enables developers to define vector database tools in YAML and expose them to LLMs through the Model Context Protocol (MCP). It eliminates the need to write custom MCP se…
→ View original sourceYour AI Agent Takes 12 Seconds. The LLM Takes 2. Where Did the Other 10 Seconds Go?
Production agent latency is rarely just an LLM problem. Here’s how to find the real bottleneck.Continue reading on Medium »
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LLMs could control their host machines by exploiting inference engines
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→ View original sourceMeet BBPrime: My $2k, 104gb VRAM, 256gb ram, extremely hacked together AI Rig
Just a bit of hardware NSFW, we all love a good budget rig. I'm running a decommissioned poweredge 720 (400 on Facebook marketplace) with two xeon v2s (don't remember the exact but it's the ivy b
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Ox-Alpha Is GLM?
The article titled 'Ox-Alpha Is GLM?' questions whether Ox-Alpha corresponds to a Generalized Linear Model. It was posted on Hacker News on 2026-08-24 by u/jitbit and can be read at https://dejan.ai/blog/ox-alpha/. Read …
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