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  "markdown": "Global Head, Nemotron and Post Training.\n\n- LinkedIn: https://www.linkedin.com/in/mukundhansrinivasan/\n\n## What Mukundhan builds\n\n- [Nemotron 3.5 ASR Streaming 0.6B](https://www.anchorterminal.com/tools/nemotron-3-5-asr-streaming-0-6b.md), graded C, 59.8/100, in Speech-to-text. Nemotron 3.5 ASR Streaming 0.6B is NVIDIA's open-weight streaming speech recognition model, a 600M-parameter FastConformer with an RNN-T decoder, transcribing 32 language-locales with punctuation and an optional detected-language tag at chunk sizes from 80 ms to 1.12 s, under OpenMDW-1.1. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/tools/nemotron-3-5-bolt-e4b-4gb.md), graded C, 61/100, in Open-weight models. Nemotron 3.5 Bolt E4B 4GB is NVIDIA's open-weight small language model for local voice assistants, interactive characters and device agents, post-trained from Google's Gemma 4 E4B, with 8B parameters (4B effective) and a 64K-token context. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/tools/nemotron-3-5-lightning-30b-a3b.md), graded B, 64.2/100, in Open-weight models. Nemotron 3.5 Lightning is NVIDIA's open-weight hybrid Mamba-2 and mixture-of-experts reasoning model for agents, 30B parameters with 3B active and up to 1M tokens of context, published on Hugging Face in BF16 and NVFP4 under OpenMDW-1.1. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [Nemotron 3.5 Parse](https://www.anchorterminal.com/tools/nemotron-3-5-parse.md), graded B, 66.5/100, in Document parsing \u0026 extraction. Nemotron 3.5 Parse is NVIDIA's open-weight document parser, 0.63B parameters, that turns a page image into text with layout classes, bounding boxes and reading order, and renders Markdown, HTML tables and JSON, under OpenMDW-1.1. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [Nemotron 3.5 Super VL](https://www.anchorterminal.com/tools/nemotron-3-5-super-vl.md), graded C, 59/100, in Model APIs \u0026 inference. Nemotron 3.5 Super VL is NVIDIA's open-weight vision-language model for agents, a 120B mixture of experts with 12B active parameters that reads text, images and video. NVIDIA hosts a free trial endpoint, and the weights are under OpenMDW-1.1. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b.md), graded B, 67.1/100, in Open-weight models. Nemotron 3 Nano 30B A3B is NVIDIA's open-weight hybrid Mamba-Transformer mixture of experts for reasoning and agent work, 30B parameters with 3.5B active, published on Hugging Face in BF16, FP8 and NVFP4. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [Nemotron 3 Nano 4B](https://www.anchorterminal.com/tools/nemotron-3-nano-4b.md), graded C, 56.8/100, in Open-weight models. Nemotron 3 Nano 4B is NVIDIA's open-weight small hybrid Mamba-2 and Transformer reasoning model for agents on edge devices, 4B parameters compressed from Nemotron Nano 9B v2, published in BF16, FP8 and GGUF under the NVIDIA Nemotron Open Model License. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.md), graded C, 60.7/100, in Open-weight models. Nemotron 3 Nano Omni is NVIDIA's open-weight multimodal model that takes video, audio, images and text and returns text, a hybrid Mamba-Transformer mixture of experts with about 31B parameters and 3B active, published in BF16, FP8 and NVFP4. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b.md), graded B, 66.2/100, in Open-weight models. Nemotron 3 Super is NVIDIA's open-weight hybrid Mamba-2 and mixture-of-experts reasoning model for agents, 120B parameters with 12B active, published on Hugging Face in BF16, FP8 and NVFP4 under the NVIDIA Nemotron Open Model License. Global Head, Nemotron and Post Training, researched 2026-10-27.\n- [Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/tools/nemotron-3-ultra-550b-a55b.md), graded B, 68.8/100, in Open-weight models. Nemotron 3 Ultra is NVIDIA's largest open-weight hybrid Mamba-2 and latent mixture-of-experts reasoning model for agents, 550B parameters with 55B active and up to 1M tokens of context, published on Hugging Face in BF16 and NVFP4 under OpenMDW-1.1. Global Head, Nemotron and Post Training, researched 2026-10-27.\n\n## Works with\n\n- [Chris Malachowsky](https://www.anchorterminal.com/people/chris-malachowsky/), Co-founder, NVIDIA\n- [Curtis Priem](https://www.anchorterminal.com/people/curtis-priem/), Co-founder, NVIDIA\n- [Ganesh K.](https://www.anchorterminal.com/people/ganesh-k/), System Software Manager; NeMo Guardrails product strategy and engineering lead\n- [Jensen Huang](https://www.anchorterminal.com/people/jensen-huang/), Co-founder, NVIDIA\n- [Nithin Rao Koluguri](https://www.anchorterminal.com/people/nithin-rao-koluguri/), Senior Research Scientist; Parakeet-TDT-0.6B-v3 paper co-author\n- [Sean Sodha](https://www.anchorterminal.com/people/sean-sodha/), Senior Software Product Manager, Nemotron RAG \u0026 Generative AI\n\n## Questions\n\n### Who is Mukundhan Srinivasan?\n\nMukundhan Srinivasan is global Head at Nemotron and Post Training.\n\n### What does NVIDIA make?\n\nAnchor Terminal lists Nemotron 3.5 ASR Streaming 0.6B, NVIDIA Nemotron 3.5 Bolt E4B 4GB, Nemotron 3.5 Lightning 30B A3B, Nemotron 3.5 Parse, Nemotron 3.5 Super VL, Nemotron 3 Nano 30B A3B, Nemotron 3 Nano 4B, Nemotron 3 Nano Omni 30B A3B Reasoning, Nemotron 3 Super 120B A12B and Nemotron 3 Ultra 550B A55B from NVIDIA. Nemotron 3.5 ASR Streaming 0.6B is NVIDIA's open-weight streaming speech recognition model, a 600M-parameter FastConformer with an RNN-T decoder, transcribing 32 language-locales with punctuation and an optional detected-language tag at chunk sizes from 80 ms to 1.12 s, under OpenMDW-1.1.\n\n### How are Mukundhan's tools graded?\n\nNemotron 3.5 ASR Streaming 0.6B is graded C, 59.8 out of 100; NVIDIA Nemotron 3.5 Bolt E4B 4GB is graded C, 61 out of 100; Nemotron 3.5 Lightning 30B A3B is graded B, 64.2 out of 100; Nemotron 3.5 Parse is graded B, 66.5 out of 100; Nemotron 3.5 Super VL is graded C, 59 out of 100; Nemotron 3 Nano 30B A3B is graded B, 67.1 out of 100; Nemotron 3 Nano 4B is graded C, 56.8 out of 100; Nemotron 3 Nano Omni 30B A3B Reasoning is graded C, 60.7 out of 100; Nemotron 3 Super 120B A12B is graded B, 66.2 out of 100; Nemotron 3 Ultra 550B A55B is graded B, 68.8 out of 100, on Anchor Terminal's benchmark, which scores every listing against the same checklist.\n\n## Sources\n\n- https://www.linkedin.com/in/mukundhansrinivasan/\n- https://developer.nvidia.com/nemotron\n- https://www.linkedin.com/in/sean-sodha/details/experience/\n- https://huggingface.co/blog/nvidia/nemotron-retriever-world-class-agentic-retrieval\n- https://www.linkedin.com/in/sean-sodha\n- https://huggingface.co/nvidia/Nemotron-3.5-Parse\n- https://www.nvidia.com/en-gb/\n- https://www.nvidia.com/en-gb/contact/\n\nThese are the people building the tools we list, named for their public role in the company or project behind a listing, from public pages, with the date it was researched. They don't work for Anchor Terminal (our own team is on the about page, /about/#author). We show public roles, public profiles and what the listing pages show, nothing private. To correct something, send an about or a photo, or have a page removed, write to privacy@anchorterminal.com.\n",
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