--- title: NVIDIA Nemotron 3 Ultra: 10x cheaper than GPT-4o | daily.dev description: NVIDIA released Nemotron 3 Ultra, a 550B-parameter open-weights Mixture-of-Experts model combining Transformer and Mamba layers, positioned as roughly 10x... canonical: https://daily.dev/posts/nvidia-nemotron-3-ultra-10x-cheaper-than-gpt-4o-7r1ve6mgp twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: NVIDIA Nemotron 3 Ultra: 10x cheaper than GPT-4o | daily.dev og:description: NVIDIA released Nemotron 3 Ultra, a 550B-parameter open-weights Mixture-of-Experts model combining Transformer and Mamba layers, positioned as roughly 10x... og:url: https://daily.dev/posts/nvidia-nemotron-3-ultra-10x-cheaper-than-gpt-4o-7r1ve6mgp og:image: https://api.daily.dev/og/posts/7r1ve6mGp.png og:image:alt: NVIDIA Nemotron 3 Ultra: 10x cheaper than GPT-4o og:image:width: 1200 og:image:height: 630 og:locale: en --- [FireUp](https://daily.dev/sources/fireup-pro) [Read post](https://api.daily.dev/r/7r1ve6mGp) # [NVIDIA Nemotron 3 Ultra: 10x cheaper than GPT-4o](https://api.daily.dev/r/7r1ve6mGp "Go to post") This title could be clearer and more informative. Try out Clickbait Shield for free (5 uses left this month). NVIDIA released Nemotron 3 Ultra, a 550B-parameter open-weights Mixture-of-Experts model combining Transformer and Mamba layers, positioned as roughly 10x cheaper than GPT-4o on enterprise agent benchmarks. It offers a 1M token context window (vs GPT-4o's 256K), 5x faster throughput than comparable open models, and 30% fewer tokens per task. The OpenMDW-1.1 license permits commercial use, and NVIDIA released training data and recipes alongside weights, enabling fine-tuning and self-hosting on Blackwell, Hopper, or Ampere GPUs via NVFP4 quantization. Deployment options include NVIDIA NIM microservices (OpenAI-compatible REST API), bare-metal self-hosting via Hugging Face, or managed NVIDIA AI Enterprise. Switching from GPT-4o makes most sense for teams with NVIDIA hardware, long-context workflows, private fine-tuning needs, or air-gapped/sovereign deployment requirements. [#open-source](/tags/open-source "Check all #open-source posts")[#llm](/tags/llm "Check all #llm posts")[#gpt](/tags/gpt "Check all #gpt posts")[#mixture-of-experts](/tags/mixture-of-experts "Check all #mixture-of-experts posts") Sep 03 • 4m read time • From [fireup.pro](https://api.daily.dev/r/7r1ve6mGp "fireup.pro") [](https://api.daily.dev/r/7r1ve6mGp "Go to post") Table of contents [What is NVIDIA Nemotron 3 Ultra?](https://api.daily.dev/r/7r1ve6mGp "What is NVIDIA Nemotron 3 Ultra?")[ Nemotron 3 Ultra vs GPT-4o](https://api.daily.dev/r/7r1ve6mGp "Nemotron 3 Ultra vs GPT-4o")[ What open weights actually mean for your team?](https://api.daily.dev/r/7r1ve6mGp "What open weights actually mean for your team?")[ Why it’s built for agents?](https://api.daily.dev/r/7r1ve6mGp "Why it’s built for agents?")[ How to deploy it?](https://api.daily.dev/r/7r1ve6mGp "How to deploy it?")[ Is it worth switching from GPT-4o?](https://api.daily.dev/r/7r1ve6mGp "Is it worth switching from GPT-4o?") Questions this post answers How does NVIDIA Nemotron 3 Ultra compare to GPT-4o on context window and cost? Nemotron 3 Ultra offers a 1,000,000 token context window versus GPT-4o's 256,000, and runs roughly 10x cheaper on enterprise agent benchmarks. It also uses about 30% fewer tokens per task and delivers 5x faster throughput than comparable open models. Unlike GPT-4o, it ships with open weights under the OpenMDW-1.1 license, permitting self-hosting and fine-tuning. Teams weighing a move off GPT-4o can track model cost and context comparisons like this on daily.dev. What hardware do I need to self-host NVIDIA Nemotron 3 Ultra? Self-hosting requires NVIDIA hardware: Blackwell, Hopper, or Ampere GPUs, with NVFP4 quantization natively supported across all three for minimal accuracy loss. Weights are available on Hugging Face, and deployment options include NVIDIA NIM microservices with an OpenAI-compatible REST API running on Kubernetes, or managed deployment through NVIDIA AI Enterprise. Anyone planning self-hosted inference infrastructure follows hardware and deployment specifics like these on daily.dev. Is Nemotron 3 Ultra a Mixture-of-Experts model and how big is it? Yes, Nemotron 3 Ultra is a Mixture-of-Experts model with 550 billion total parameters and 55 billion active per token, combining Transformer layers for precise retrieval with Mamba sequence modeling for efficient long-sequence handling. It was trained using Multi-Teacher On-Policy Distillation, with over 10 specialized teacher models scoring outputs across reasoning, coding, tool use, and domain logic. Engineers evaluating MoE architectures for agent workloads keep up with releases like this on daily.dev. 28 Upvotes4 Comments1 Repost Comment Bookmark Copy Share your thoughts Post [](https://daily.dev/sources/fireup-pro) [FireUp](https://daily.dev/sources/fireup-pro "https://daily.dev/sources/fireup-pro") 29 Followers • 364 Upvotes #### Would you recommend this post? Copy link WhatsApp Facebook X New Squad Copy linkShare with your friends 28 4 ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"NVIDIA Nemotron 3 Ultra: 10x cheaper than GPT-4o","url":"https://daily.dev/posts/nvidia-nemotron-3-ultra-10x-cheaper-than-gpt-4o-7r1ve6mgp","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/nvidia-nemotron-3-ultra-10x-cheaper-than-gpt-4o-7r1ve6mgp"},"datePublished":"2026-09-03T10:37:09.483Z","dateModified":"2026-09-07T12:07:32.721Z","description":"NVIDIA released Nemotron 3 Ultra, a 550B-parameter open-weights Mixture-of-Experts model combining Transformer and Mamba layers, positioned as roughly 10x...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/18760d8027fdbab75a06392e5f6e9253?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/18760d8027fdbab75a06392e5f6e9253?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"FireUp","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"FireUp","logo":"https://media.daily.dev/image/upload/s--JWZsm71i--/f_auto,q_auto/v1774960866/logos/fireup-pro?_a=BAMAMiWQ0","url":"https://daily.dev/sources/fireup-pro"},"commentCount":4,"discussionUrl":"https://daily.dev/posts/nvidia-nemotron-3-ultra-10x-cheaper-than-gpt-4o-7r1ve6mgp","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":28},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":4}],"keywords":"open-source,llm,gpt,mixture-of-experts","timeRequired":"PT4M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"FireUp","item":"https://daily.dev/sources/fireup-pro"},{"@type":"ListItem","position":3,"name":"NVIDIA Nemotron 3 Ultra: 10x cheaper than GPT-4o"}]} {"@context":"https://schema.org","@type":"WebPage","@id":"https://daily.dev/posts/nvidia-nemotron-3-ultra-10x-cheaper-than-gpt-4o-7r1ve6mgp","comment":[{"@type":"Comment","text":"Cool I guess this will be worth giving a couple pulls to see how it is. Nemotron 3 was ok, it’s a fast and powerful model but is tough to steer. You need to nail the context or it goes off track.","datePublished":"2026-09-03T12:35:48.071Z","url":"https://daily.dev/posts/7r1ve6mGp#c-Mxf16pERL","author":{"@type":"Person","name":"Peter Cruckshank","url":"https://daily.dev/petecapecod","image":"https://media.daily.dev/image/upload/s--ZJhQyKws--/f_auto/v1721235024/avatars/avatar_A9xh33q0QoxtkGoJRCosp"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":3}},{"@type":"Comment","text":"Am i missing something here? What is the point of comparing new model to GPT-4o? Anybody using 4o for anything still?","datePublished":"2026-09-04T09:17:05.876Z","url":"https://daily.dev/posts/7r1ve6mGp#c-Eq056gjqZ","author":{"@type":"Person","name":"Jakub","url":"https://daily.dev/jakoss","image":"https://avatars.githubusercontent.com/u/3933348?v=4"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":3}},{"@type":"Comment","text":"Ten times cheaper sounds great, but I’d want to see the receipt from one real agent run on the actual GPU. Long context can make self-hosting math weird fast.","datePublished":"2026-09-04T22:41:45.234Z","url":"https://daily.dev/posts/7r1ve6mGp#c-M6PVaB6hC","author":{"@type":"Person","name":"Agustin Barrientos","url":"https://daily.dev/agustinbarrientos","image":"https://media.daily.dev/image/upload/s--5ayxQnqn--/f_auto/v1788281802/avatars/avatar_wQYYVe5Tbj0NJ7C7qPoa8?_a=BAMAMicg0"}}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/nvidia-nemotron-3-ultra-10x-cheaper-than-gpt-4o-7r1ve6mgp#faq","mainEntity":[{"@type":"Question","name":"How does NVIDIA Nemotron 3 Ultra compare to GPT-4o on context window and cost?","acceptedAnswer":{"@type":"Answer","text":"Nemotron 3 Ultra offers a 1,000,000 token context window versus GPT-4o's 256,000, and runs roughly 10x cheaper on enterprise agent benchmarks. It also uses about 30% fewer tokens per task and delivers 5x faster throughput than comparable open models. Unlike GPT-4o, it ships with open weights under the OpenMDW-1.1 license, permitting self-hosting and fine-tuning. Teams weighing a move off GPT-4o can track model cost and context comparisons like this on daily.dev."}},{"@type":"Question","name":"What hardware do I need to self-host NVIDIA Nemotron 3 Ultra?","acceptedAnswer":{"@type":"Answer","text":"Self-hosting requires NVIDIA hardware: Blackwell, Hopper, or Ampere GPUs, with NVFP4 quantization natively supported across all three for minimal accuracy loss. Weights are available on Hugging Face, and deployment options include NVIDIA NIM microservices with an OpenAI-compatible REST API running on Kubernetes, or managed deployment through NVIDIA AI Enterprise. Anyone planning self-hosted inference infrastructure follows hardware and deployment specifics like these on daily.dev."}},{"@type":"Question","name":"Is Nemotron 3 Ultra a Mixture-of-Experts model and how big is it?","acceptedAnswer":{"@type":"Answer","text":"Yes, Nemotron 3 Ultra is a Mixture-of-Experts model with 550 billion total parameters and 55 billion active per token, combining Transformer layers for precise retrieval with Mamba sequence modeling for efficient long-sequence handling. It was trained using Multi-Teacher On-Policy Distillation, with over 10 specialized teacher models scoring outputs across reasoning, coding, tool use, and domain logic. Engineers evaluating MoE architectures for agent workloads keep up with releases like this on daily.dev."}}]} ```