Nemotron 3.5 Bolt
Run everyday agentic tasks locally on a 24GB GPU
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Nemotron 3.5 Bolt 24GB is NVIDIA’s model for running everyday agentic tasks locally on NVIDIA RTX and DGX Spark hardware. It compresses Nemotron 3.5 Super VL from 120B total, 12B active to 74B total, 9B active, sized to fit a 24GB memory budget. NVIDIA reports 84 tokens per second on RTX Spark. Text and vision. Checkpoints, GGUF files, and a speculative-decoding drafter are on Hugging Face.
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PH · launched Oct 17, 2026 · 11 upvotes (top 4%)
- Horizontal
- Model & infra
- Developer
- AI-native
- Commercial product
- Artificial Intelligence
Similar launches
See all 192 similar launches →Could you build this?
No This is an enterprise-grade 74B parameter pruned/quantized vision-language foundation model trained and released by NVIDIA, requiring immense compute clusters and advanced machine learning research.
What it would actually take: Training or compressing a 74B parameter multimodal model requires thousands of high-end GPUs (e.g., H100 clusters), distributed training frameworks (Megatron-LM, TensorRT-LLM), massive multimodal pretraining datasets, and specialized knowledge in model pruning, distillation, and quantization. Vibe coding cannot recreate foundation model weights or access the necessary multi-million-dollar compute infrastructure.
Competitors
Other products that read as similar to this one : 192 launches clear the similarity bar, closest 8 shown.
Attention rank: #11 of 193 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 344 days after the earliest competitor.
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