Open-source model Neon mid-trained on 1,300 H200s claims to beat GPT-6 Astra
bookwormengr · x · 2026-09-16
The quoted post says the team built high-throughput materials labs in Menlo Park to create a loop between experiments and models: the labs generate fresh data, the models learn from it, and then help decide what to try next.
Using only 1,300 H200s plus months of experimental data, they mid-trained and RL'd an open-source model to surpass GPT-6 Astra on their analysis benchmark, calling it Neon.
The post claims this is real footage. The claim comes from the quoted tweet and has not been independently verified.
More from Models
- 'You Can Feel the Gradient Slopes': Dev Contrasts Benchmaxxed RL Models vs General Ones — theteknosaur · 2026-11-02
- LightOnOCR-3 Launches: Tops FRBench, Adds Layout Structure and Chart Extraction — IgorCarron · 2026-11-02
- NVIDIA's Kumo Is a Family of Four Tabular Foundation Models, Not Just One — pandeyparul · 2026-11-02
- SemiAnalysis: safety classifiers are underrated — Meta's Muse tops cyber benchmark at 35.2% — ThomasScialom · 2026-11-02
- DeepSeek V4.1 Flash 1017 wins over a longtime closed-source-only user: fast, cheap, reliable — _bachrc · 2026-11-02
- Local quants vs Claude on 9 real private bugs: 3-bit costs thinking time, not score — FeydRowan · 2026-11-02