NVIDIA Blackwell

Model ● Covered in 4 stories Compare ⇄ + Follow

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Latest developments

Performance per dollar is getting faster and cheaper TLDR Dev · 4 weeks ago · 25

Inside the Together AI kernels team Together AI · 4 months ago · 20

Optimizing inference speed and costs: Lessons learned from large-scale deployments Together AI · 6 months ago · 34

Bringing 100,000 GPUs to Europe Together AI · 1 year ago · 28

Timeline

Month Quarter Year

2026

2025

12 Jun Bringing 100,000 GPUs to Europe

Relationships

Products & technology

Together AI deploys this model · 1 source
NVIDIA develops this model · 1 source

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TLDRocket 3 August 2026

Open-source AI models are consolidating their foothold as the dominant deployment pattern, even as frontier capabilities remain concentrated at a handful of well-funded labs. Interconnects launched the Artifacts Hub and Adoption Dashboard to track 792 open-weight models released in two years, mapping adoption by geography and revealing how deeply DeepSeek and Chinese models have penetrated deployment pipelines globally. Meanwhile, DeepSeek itself proved that scale isn't everything: its V4-Flash model, a leaner 284-billion-parameter variant, outperformed its own flagship on agent benchmarks through careful post-training. The MIT-licensed release lets enterprises avoid vendor lock-in entirely, directly controlling deployment and retraining at lower infrastructure cost.

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