📊 BENCHMARKS & EVALS
- Reddit user benchmarks 21 Qwen3.8-27B quants on 16GB VRAM
A Reddit user benchmarked 21 Qwen3.8-27B quantizations on a 16GB GPU.- The comparison targets local-LLM users running Qwen3.8-27B on 16GB GPUs, including an RTX 5080.
- The benchmark tested 21 variants against real C code.
- bartowski/Qwen3.8-27B-IQ4_XS ranked best overall; Huihui-Qwen3.8-27B-abliterated-UD-IQ4_XS ranked best among uncensored variants.
- The results compare which quantizations fit on 16GB VRAM and how they perform on coding workloads.
Sources 📎 Coverage: reddit.com · 👁 via r/LocalLLaMA
💰 BUSINESS & FUNDING
- Nscale seeks $3.5B in pre-IPO financing from Nvidia and Third Point
Nscale is seeking up to $3.5 billion in pre-IPO financing ahead of a planned U.S. listing.- Nscale provides GPU-powered AI compute through its data centers, hardware, and software stack.
- The company is seeking up to $1.5 billion in convertible notes led by Third Point and about $2 billion from Nvidia.
- The notes would convert at a double-digit discount to the IPO price, with the conversion price capped at a $30 billion valuation.
- Nscale has reported roughly $103 billion in contracted business, including a six-year, $45 billion Anthropic computing agreement.
- The financing would precede Nscale’s planned New York listing, though the investors and deal size remain subject to change.
Sources 📎 Coverage: thenextweb.com · 👁 via TechCrunch AI