You already gave the LLM the answer. So why is it writing it out from scratch? Introducing a new AI model architecture: Constrained Decoding Models (CDMs) LLMs were built to write. Most production workloads just need an answer: fast, consistent, and affordable. CDMs are purpose-built for 1 task each. They read your input once and skip the token-by-token generative loop that makes LLMs slow and expensive. Not just a decision model, but a family of 3 CDMs live today: • Classify: define your labels and get back a calibrated probability + reason for each. Used for routing, tagging, and intent detection. • Extract: describe the entities in natural language and get back well-formed JSON with confidence scores + citations. Used for web scraping, document processing, and PII redaction. • Summarize: pass in long text, images, or PDFs and get back a consistent summary under 1,000 tokens. Used for context compaction, metadata generation, and transcript digests. Built for production: • 1M tokens of multimodal (text + image) input, 31x larger than Jev • 77.2% on DecisionBench vs Jev's 72% • 200x faster, 467x cheaper than frontier LLM APIs • $0.05/M input tokens. Output is free (yes, even for summarize) Live on your favorite platforms today: @OpenRouter @vercel_dev @LiteLLM @LangChain @TrustedRouter @itsArthurAI @useRouterPlus Get 50M input tokens for free (for the first 50 hours) at link below 👀
Videoda söylenenler:
“Your model already read the answer, so why is it still typing? Introducing Constrained Decoding Models. Both LLMs and CDMs read your context in one pass. Traditional LLMs slowly write the answer, one token at a time. Scale-down CDMs know the answer is already there, so we poin...”
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{ "aciklama": "Video, geleneksel büyük dil modellerinin (LLM) veriyi yavaşça tek tek yazdığını, buna karşılık yeni 'Constrained Decoding Models' (CDM) mimarisinin cevabı doğrudan işaret ederek çok daha hızlı ve ucuz bir şekilde sunduğunu anlatıyor. Görsel olarak bir faturadan veri çıkarma örneği üzerinden bu hız farkını karşılaştırmalı olarak gösteriyor.", "yazilar": "Kare 1:\nYour\nalready\nLLM\nread\nthe\nanswer\n\nKare 2:\nINVOICE\nNo. 2026-0418\nTerms: Net 30\nFROM\nHalcyon Supply Co.\n41 Mercer Row, Leeds LS1 4AB\nBILL TO\nNorthwind Traders Ltd.\n4 Quay Street, Bristol\nINVOICE DATE\n2026-10-06\nDUE DATE\n2026-11-05\nCURRENCY\nUSD\nDESCRIPTION\nQTY\nAMOUNT\nInference credits, Sept\n1\n2,400.00\nPriority support plan\n1\n1,200.00\nBatch processing, 40M tokens\n4\n980.00\nOnboarding workshop\n1\n240.00\nSubtotal\n4,820.00\nTax (0%)\n0.00\nTotal\nUSD 4,820.00\nPay to: Halcyon Supply Co. IDAN 2020 0418 1351 0208 19.\nThank you for your business.\nSO WHY IS IT STILL TYPING?\nQuestion:\nWhat is the Supplier Name, Date, and\nCurrency?\nAnswer:\n{\n\"supplier\"\n\nKare 3:\nConstrained\nDecoding\n\nKare 4:\nTRADITIONAL LLM\nINVOICE\nNo. 2026-0418\nTerms: Net 30\nFROM\nHalcyon Supply Co.\n41 Mercer Row, Leeds LS1 4AB\nBILL TO\nNorthwind Traders Ltd.\n4 Quay Street, Bristol\nINVOICE DATE\n2026-10-06\nDUE DATE\n2026-11-05\nCURRENCY\nUSD\nDESCRIPTION\nQTY\nAMOUNT\nInference credits, Sept\n1\n2,400.00\nPriority support plan\n1\n1,200.00\nBatch processing, 40M tokens\n4\n980.00\nOnboarding workshop\n1\n240.00\nSubtotal\n4,820.00\nTax (0%)\n0.00\nTotal\nUSD 4