Nemotron 3.5 Super VL

Headlines · 3

1. 16h
   NVIDIA and AI4Bharat to release 2.8T-token Indic pretraining corpus and open pipeline

   NVIDIA and AI4Bharat, IIT Madras' Indian-language research lab, are releasing Nemotron-pretraining-Indic-v1, a corpus of roughly 2.8 trillion tokens across the 22 languages listed in India's Constitution — 2,601.0 billion native-script tokens and 224.6 billion romanized tokens under the Gemma-4 tokenizer, spanning 34 language-script configurations. It was built from 15 Nemotron-CC-v2 subsets with NeMo Data Designer running document-level translation, MQM-style quality scoring with a 75/100 threshold and targeted repair, while retaining source identifiers so each output traces back to a real document; NVIDIA is also open-sourcing the GPU-accelerated generation pipeline. Continued pretraining for Nemotron 3.5 Super VL added 10 billion Indic tokens, 10% of a 100-billion-token budget, and the technical report reports gains of 4.98 to 9.82 points on five Indic knowledge and reasoning benchmarks, though that comparison mixes synthetic and natural Indic data.

   Hugging Face · 🔥 7
2. 1d
   Prime Intellect and NVIDIA post-train Nemotron 3.5 Super VL for enterprise agents

   Prime Intellect and NVIDIA built a 2,500-task verified enterprise dataset and ran 100 GRPO steps (about 11 hours on 128 NVIDIA GB200 GPUs) to lift NVIDIA Nemotron 3.5 Super VL from 34.0% at its SFT checkpoint to 57.7% on the public split of AutomationBench-AA, a 23.7-point gain. The tasks span 47 simulated SaaS applications such as CRMs, inboxes, help desks and spreadsheets, and scoring inspects only the final application state: partial credit for objectives met, zeroed if any guardrail is violated. The post says every task is attacked with scripted shortcuts (blanket actions, doing nothing, claiming success) before admission, with about 18,000 attempts in the latest batches getting through none, and a second independent grader matching scores byte for byte on roughly 69,000 episodes.

   Prime Intellect Blog · 🔥 5
3. 2d
   NVIDIA releases Nemotron 3.5 Super VL and two Bolt edge models

   NVIDIA released Nemotron 3.5 Super VL on Oct. 15, an open multimodal model with 120B total and 12B active parameters in a mixture-of-experts design that combines reasoning, instruction following and tool use with text, image, document and video understanding for long-running agents. NVIDIA claims it reaches up to 5x the agentic throughput of other open models in its size class on a single GPU — over 600 output tokens per second at 100,000 input tokens — scores 80.8% on the CharXiv chart-reasoning benchmark (84% with Python code interpretation), and supports NVFP4 quantization and multi-token prediction; BF16 and NVFP4 weights are on Hugging Face with same-day vLLM and Baseten support. Alongside it, NVIDIA launched two Nemotron 3.5 Bolt edge models: Bolt 74B-A9B 24GB, which uses native 2-bit quantization to fit in 24GB of memory and is available now, and Bolt E4B 4GB, due Oct. 23.

   vLLM Blog · 🔥 71

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