NVIDIA

The official handle for NVIDIA.

5.0•27 reviews•

2.2K followers

The official handle for NVIDIA.

5.0•27 reviews•

2.2K followers

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AI Infrastructure Tools

NVIDIA, inventor of the GPU, which creates interactive graphics on laptops, workstations, mobile devices, notebooks, PCs, and more. We created the world’s largest gaming platform and the world’s fastest supercomputer. We are the brains of self-driving cars, intelligent machines, and IoT.

This is the 31st launch from NVIDIA. View more

Nemotron 3 Ultra by NVIDIA

Launched this week

Powers faster, efficient reasoning for long-running agents

A 550B MoE frontier-intelligence open model built for long-running agents. It delivers 5x faster inference and lowers the cost of complex agentic tasks by up to 30% versus other open frontier models.Ultra excels at complex tasks like coding and deep research. Long-running agents spend their time planning, using tools, recovering from failures, and deciding what to do next.

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Launch tags:Developer Tools•Artificial Intelligence

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FramerLaunch websites with enterprise needs at startup speeds.

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Previous NVIDIA Launches

NVIDIA Nemotron 3 UltraThe first open frontier model built for agents

Launched on June 5th, 2026

NVIDIA NemoClawRun autonomous agents more safely

Launched on March 19th, 2026

DLSS 5The GPT moment for real-time computer graphics

Launched on March 17th, 2026

Nemotron 3 SuperOpen hybrid Mamba-Transformer MoE for agentic reasoning

Launched on March 13th, 2026

View all NVIDIA launches

5.0

Based on 27 reviews

Review NVIDIA?

Reviewers are almost entirely founders, and their feedback is narrow but clear: NVIDIA is seen as core infrastructure for AI work, especially through CUDA, GPU optimization, and tools for training, inference, and video workloads. Makers of TwelveLabs, aperture, and ClawMetry describe strong performance, a deep ecosystem, and reliable scaling, with added value from NVIDIA Inception support. There are no meaningful user reviews here, and almost no direct criticism, so the picture is positive but one-sided.

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Summarized with AI

Pros

CUDA optimization (4)

powerful GPUs (3)

developer experience (2)

fast performance (2)

Pros

Cons

Reviews

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Most Informative

used NVIDIA to build Doza Assist

•4 reviews

Shoutout to NVIDIA for Parakeet. Doza Assist runs dual-engine transcription locally on the editor's Mac, and Parakeet is the primary engine. It's fast, accurate, and runs beautifully on Apple Silicon. When you drop a 90-minute documentary interview into Doza Assist and get back a word-level timestamped transcript in minutes without anything leaving your machine, that's Parakeet doing the heavy lifting. NVIDIA built a transcription model that competes with cloud APIs while running entirely on local hardware. That's what makes local-first AI editing possible, not theoretical.

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used NVIDIA to build Ailytics instead of Gemini

•3 reviews

NVIDIA's edge AI stack and AI models such as CUDA, TensorRT, Cosmos is the core backbone of Ailytics' AI's real-time video across all our projects. The Inception program gave us GTM support and early access to special models and customer introductions, which we're now using for industrial contextual scene handling whilst being compute efficient at the same time.

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Gemini

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2 views1mo ago

used NVIDIA to build aperture

•3 reviews

NVIDIA gave us the best balance of performance, ecosystem, and long-term reliability. Their GPU stack is the industry standard for AI workloads, and being part of NVIDIA Inception gave us early access, support, and credibility. For a system like ours that depends on consistent model performance and scaling, that stability mattered more than experimenting with fragmented providers.

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1 view2mo ago