Nvidia-backed Reflection AI raises $2 billion in funding, boosts valuation to $8 billion - AI2Work Analysis

Reflection AI – Nvidia‑Backed $2B Milestone Drives Open‑Source LLMs (2025) { "@context": "https://schema.org", "@type": "Article", "headline": "Reflection AI – Nvidia‑Backed $2B Milestone Drives Open‑Source LLMs (2025)", "author": { "@type": "Person", "name": "Alex Mercer" }, "datePublished": "2025-10-12", "keywords": [ "Reflection AI", "open-source LLM", "Nvidia H100", "GPT‑4 Turbo", "200–300 B parameters", "AI enterprise adoption" ], "articleBody": " " } { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [ { "@type": "Question", "name": "What hardware is required for fine‑tuning Reflection AI?", "acceptedAnswer": { "@type": "Answer", "text": "Fine‑tuning a 200–300 B‑parameter model on Reflection AI typically requires at least four Nvidia H100 GPUs with 80 GB memory each, running the Hopper‑optimized training stack." } }, { "@type": "Question", "name": "How does Reflection AI compare to GPT‑4 Turbo on MMLU?", "acceptedAnswer": { "@type": "Answer", "text": "Reflection AI reports a 12–15 % higher score on the MMLU benchmark, achieving an average of 72.3 % versus GPT‑4 Turbo’s 64.8 % as of September 2025." } }, { "@type": "Question", "name": "What is the estimated inference latency on Nvidia H100s?", "acceptedAnswer": { "@type": "Answer", "text": "Inference latency for a single prompt averages 42 ms on an H100, representing an 8–10 % speedup over comparable models like GPT‑4 Turbo." } } ] } figure img{max-width:100%;height:auto;} figcaption{text-align:center;font-style:italic;color:#555;} Reflection AI – Nvidia‑Backed $2B Milestone Drives Open‑Source LLMs (2025) Reflection AI has secured a record $2 billion Series‑B round led by Nvidia, catapulting the startup to an $8 billion valuation. The investment fuels its ambition to deliver a 200–300 B‑parameter open‑source large language model (LLM) that outperforms GPT‑4 Turbo and Claude 3.5 on reasoning benchmarks while delivering faster inference on Nvidia H100 GPUs. Why the $2B Investment Matters for En