iFANN
    Buscar no iFANN...
    Entrar
    Início
    Notícias
    Vídeos
    Fotos
    GIFs
    Explorar
    Enquetes
    Prêmios
    iFAMOUS
    Wiki
    Anime
    Salas
    Notificações
    Mensagens
    Salvos
    Perfil
    WikiPrêmiosiFAMOUSRankingsSetoresRecompensas para criadoresRecompensas para usuáriosTermosPrivacidadeDiretrizes da comunidadeRemoção / DMCAAjudaDesenvolvedores

    © 2026 iFANN

    Início
    Buscar
    Mensagens
    Alertas
    Perfil
    Foto
    Ts Floyd
    Ts Floyd@ts_floyd1h
    🏢Nvidia🏢Georgia Tech - Georgia Institute of Technology💭AI
    Small Language Models Future Agentic AI

    @ts_floydMost agent calls involve small decisions like routing, classifying, checking, or gating. These tasks do not require frontier models because an agent loop primarily consists of bounded choices rather than deep reasoning. Post-training methods such as SFT and RL against verifiers are becoming more important than raw model size. A 3B parameter model quantized to int4 fits in approximately 1.5 GB and runs on a laptop. API traffic can be distilled into a proprietary model with hard cases escalated. At high volume, owning models becomes more cost-effective than renting within days. TwIL-LM3-Pro by thewebai has 3.6 billion parameters. It performs on par with Qwen3-8B on formal logic tasks and leads VibeThinker-3B on all six tested formal-logic tasks. TwIL-LM3-Pro occupies 2.09 GiB and runs on CPU or 4GB VRAM. Every agent will incorporate a layer of small specialists underneath it. Small Language Models are positioned as the future of Agentic AI. An 18-page PDF containing full details is available. The TwIL-LM3-Pro model is hosted at http://huggingface.co/webAI-Official/TwIL-LM3-Pro.

    Ver publicação original

    Small Language Models Future Agentic AI

    Foto de @ts_floyd· Oct 2, 2026· Nvidia

    Sobre esta foto

    This is a screenshot of a research paper titled "Small Language Models are the Future of Agentic AI." The focus is the paper's title, authors, and abstract. The mood is academic and informative. A notable detail is the arXiv watermark on the left side. ON-SCREEN TEXT: Small Language Models are the Future of Agentic AI. Peter Belcak, Greg Heinrich, Shizhe Diao, Yonggan Fu, Xin Dong, Saurav Muralidharan, Yingyan Celine Lin, Pavlo Molchanov. NVIDIA Research, Georgia Institute of Technology. [email protected]. Abstract. 1 Introduction. Pre-print. Under review.

    Ver todas as fotos de NvidiaLer a wiki de Nvidia

    ?

    Mais fotos de Nvidia

    Ver todas as fotos de Nvidia
    Nvidia stock chart record highNvidia stock chart record highWorld's biggest companies profit per $100 revenueWorld's biggest companies profit per $100 revenueNvidia truck heist fails2Nvidia truck heist failsJensen Huang low IQ era AI education2Jensen Huang low IQ era AI educationJensen Huang AI surgery comparison2Jensen Huang AI surgery comparisonJensen Huang World Economic Forum AI speech2Jensen Huang World Economic Forum AI speechDonald Trump AI hoax statement2Donald Trump AI hoax statementJensen Huang Nvidia AI strategy2Jensen Huang Nvidia AI strategyElon Musk SpaceX Nvidia AI2Elon Musk SpaceX Nvidia AIDeepSeek V4.1 Flash NVFP4 locallyDeepSeek V4.1 Flash NVFP4 locallymost valuable assets by market cap september 2026most valuable assets by market cap september 2026Jensen Huang AGI has arrived GPT-6 Astra2Jensen Huang AGI has arrived GPT-6 AstraNvidia acquires Hugging FaceNvidia acquires Hugging FaceGTA V RTX 6070 vs RTX 5090 comparisonGTA V RTX 6070 vs RTX 5090 comparisonDLSS 5 visual comparisonDLSS 5 visual comparisonDLSS 5 comparison NVIDIADLSS 5 comparison NVIDIATrump and Sheikh Tahnoon AI chip dealTrump and Sheikh Tahnoon AI chip dealNvidia $NVDA market cap gain2Nvidia $NVDA market cap gain
    Foto
    Ts Floyd
    Ts Floyd@ts_floyd1h
    🏢Nvidia🏢Georgia Tech - Georgia Institute of Technology💭AI
    Small Language Models Future Agentic AI

    @ts_floydMost agent calls involve small decisions like routing, classifying, checking, or gating. These tasks do not require frontier models because an agent loop primarily consists of bounded choices rather than deep reasoning. Post-training methods such as SFT and RL against verifiers are becoming more important than raw model size. A 3B parameter model quantized to int4 fits in approximately 1.5 GB and runs on a laptop. API traffic can be distilled into a proprietary model with hard cases escalated. At high volume, owning models becomes more cost-effective than renting within days. TwIL-LM3-Pro by thewebai has 3.6 billion parameters. It performs on par with Qwen3-8B on formal logic tasks and leads VibeThinker-3B on all six tested formal-logic tasks. TwIL-LM3-Pro occupies 2.09 GiB and runs on CPU or 4GB VRAM. Every agent will incorporate a layer of small specialists underneath it. Small Language Models are positioned as the future of Agentic AI. An 18-page PDF containing full details is available. The TwIL-LM3-Pro model is hosted at http://huggingface.co/webAI-Official/TwIL-LM3-Pro.

    Ver publicação original

    Small Language Models Future Agentic AI

    Foto de @ts_floyd· Oct 2, 2026· Nvidia

    Sobre esta foto

    This is a screenshot of a research paper titled "Small Language Models are the Future of Agentic AI." The focus is the paper's title, authors, and abstract. The mood is academic and informative. A notable detail is the arXiv watermark on the left side. ON-SCREEN TEXT: Small Language Models are the Future of Agentic AI. Peter Belcak, Greg Heinrich, Shizhe Diao, Yonggan Fu, Xin Dong, Saurav Muralidharan, Yingyan Celine Lin, Pavlo Molchanov. NVIDIA Research, Georgia Institute of Technology. [email protected]. Abstract. 1 Introduction. Pre-print. Under review.

    Ver todas as fotos de NvidiaLer a wiki de Nvidia

    ?

    Mais fotos de Nvidia

    Ver todas as fotos de Nvidia
    Nvidia stock chart record highNvidia stock chart record highWorld's biggest companies profit per $100 revenueWorld's biggest companies profit per $100 revenueNvidia truck heist fails2Nvidia truck heist failsJensen Huang low IQ era AI education2Jensen Huang low IQ era AI educationJensen Huang AI surgery comparison2Jensen Huang AI surgery comparisonJensen Huang World Economic Forum AI speech2Jensen Huang World Economic Forum AI speechDonald Trump AI hoax statement2Donald Trump AI hoax statementJensen Huang Nvidia AI strategy2Jensen Huang Nvidia AI strategyElon Musk SpaceX Nvidia AI2Elon Musk SpaceX Nvidia AIDeepSeek V4.1 Flash NVFP4 locallyDeepSeek V4.1 Flash NVFP4 locallymost valuable assets by market cap september 2026most valuable assets by market cap september 2026Jensen Huang AGI has arrived GPT-6 Astra2Jensen Huang AGI has arrived GPT-6 AstraNvidia acquires Hugging FaceNvidia acquires Hugging FaceGTA V RTX 6070 vs RTX 5090 comparisonGTA V RTX 6070 vs RTX 5090 comparisonDLSS 5 visual comparisonDLSS 5 visual comparisonDLSS 5 comparison NVIDIADLSS 5 comparison NVIDIATrump and Sheikh Tahnoon AI chip dealTrump and Sheikh Tahnoon AI chip dealNvidia $NVDA market cap gain2Nvidia $NVDA market cap gain