They provided an NVFP4 checkpoint, 124GB and runs w/ FP8 KV Cache
LLMS
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Dynamic Workflows solve context bloat by moving results to JS
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Exactly. That's the architectural insight most people gloss over. In a normal subagent setup, every result flows back into Claude's context window. More agents = more context bloat = earlier compaction = degraded quality. Dynamic Workflows solve that by moving results into JS
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GPT 5.5 beats local models; Opus 4.6 superior to 4.7/4.8
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– GPT 5.5 beats it – Nothing local comes close to GPT 5.5 yet – Opus 4.6 is better than Opus 4.7 / 4.8 I have said all of that before, dunno why you're being so aggressive
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Claude AI bills surge: Anthropic spends $500M in one month
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#Claude AI bills getting out of control, company spends $500 million in just one month – India Today https://
share.google/08ocxebz5YGSg6
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… #anthropic #openai #LLMs #LLM #AI #artificialintelligence #GenerativeAI #GenAI @SpirosMargaris @PawlowskiMario @mvollmer1 @gvalan @ipfconline1 -
Testing Opus 4.8 Model Performance in Different Harnesses
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Tried Opus 4.8 in different harnesses than Claude Code and nah this model is just stupid, good job Anthropic lol
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GPT-5.5 cheaper via API subscription, more efficient thinker
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No. GPT-5.5 is *much* cheaper building against the API directly, when using a subscription. And it's somewhat cheaper even when not using a subscription, because the Opus 4.7/4.8 is much less efficient, and because GPT-5.5 is a more efficient "thinker".
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NVIDIA Standardizes Open Model Families on Linux Foundation’s OpenMDW-1.1 for Unified Licensing
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NVIDIA is moving all four open model families – Cosmos, Isaac GR00T, Ising, Nemotron – onto the Linux Foundation's OpenMDW-1.1. Right now open-weight models come with a patchwork of software licenses that were never meant for AI plus bespoke terms with usage limits, so anyone
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Open-Weight AI Models Lag Frontier Closed-Source Models by Four Months
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According to research by EpochAI, open-weight models lag behind frontier closed-source models by four months. Four months. That's very little. And impressive at the same time.
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AI Vision Model Limitations in Object Detection Tasks
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This kind of prompt only works up to a point. If I ask it to put bounding boxes around all cars or all vehicles, it will mislabel lots of things while also hallucinating new things to label. pic.twitter.com/8B1CNnlbh5
— fofr (@fofrAI) 29 mai 2026This kind of prompt only works up to a point. If I ask it to put bounding boxes around all cars or all vehicles, it will mislabel lots of things while also hallucinating new things to label.
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OpenAI realtime translation: 70+ input languages to 13 output languages
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OpenAI for realtime translation — speak in any of 70+ input languages and translate into 13 output ones: https://t.co/BHhbqP3HbR
— Greg Brockman (@gdb) 29 mai 2026OpenAI for realtime translation — speak in any of 70+ input languages and translate into 13 output ones: