You could explicitly state that in your prompt, or build skills that dictate which model the skill uses.
LLMS
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DeepSeek-V4-Pro 1.6T Model Now Available on NVIDIA Blackwell
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Happy Friday!
— NVIDIA AI (@NVIDIAAI) 24 avril 2026
We just put DeepSeek-V4-Pro up on https://t.co/es07MrTxSs. It’s the world’s largest open source model at 1.6T parameters, and you can run it for free running on NVIDIA Blackwell GPUs.
Try the NVIDIA NIM API → https://t.co/zeWX4Y7Ipd pic.twitter.com/lNFsziIts4Happy Friday! We just put DeepSeek-V4-Pro up on http://
build.nvidia.com. It’s the world’s largest open source model at 1.6T parameters, and you can run it for free running on NVIDIA Blackwell GPUs. Try the NVIDIA NIM API → https://
build.nvidia.com/deepseek-ai/de
epseek-v4-pro?ncid=so-twit-300913
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GPT-5.5 reduces computer credits consumption for task orchestration
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You would consume less computer credits (and be able to run more tasks as a result) if you switched to GPT-5.5 as your default orchestrator. This was the number one complaint about Computer (being credits/token hungry). GPT 5.5 is more token-efficient in subagent orchestration.
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GPT-5.5 and GPT-5.5 Pro API availability announced
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GPT-5.5 and GPT-5.5 Pro are now available in the API!
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Long-Context Reasoning Limits Discovered in Automated Bug Fixing
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Congrats to the team on “The Limits of Long-Context Reasoning in Automated Bug Fixing” being accepted to ICLR 2026 The team put long-context reasoning to the test for automated bug fixing and found something surprising. Performance actually drops as context grows. Check out
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GPT-5.5 and Pro Models Underperform on BullshitBench
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BullshitBench: GPT-5.5 and 5.5-Pro update! They did NOT do well – 5.5 about the same level as GPT-5.4 (around 30-35 rank, 45% pushback). GPT-5.5-Pro did WORSE – only about 35% pushback. I must say the Pro result kind of shocked me. This is actually interesting, what this tells
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DeepSeek V4 Pro Flash Day-0 vLLM Support Long-Context
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Day-0 support for @deepseek_ai V4 Pro and Flash on vLLM — a new generation of DeepSeek model, purpose-built for tasks up to 1M tokens. Alongside the release, we're publishing a first-principles walkthrough of the new long-context attention and how we implemented it in vLLM. x.com/deepseek_ai/st…
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DeepSeek V4 Launch with SGLang Optimizations and RL Pipeline
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DeepSeek V4 by @deepseek_ai just dropped! SGLang is ready on Day 0 with a full stack of optimizations from architectures to low-level kernels. We also deliver a verified RL training pipeline in Miles (by @radixark) for V4 at launch: Native "ShadowRadix" Design: DeepSeek V4's
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Day-One Model Support Commitment for Major Releases
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"Day-one model support: every major release, compatible at launch" <- this is quite a commitment! Awesome news! Congrats!
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DeepSeek-V4 Million-Token Context LLM Agentic Workflows
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DeepSeek-V4 is here — a million-token context, 1.6T parameter powerhouse optimized for agentic workflows. Out of the box, on DeepSeek-V4-Pro, NVIDIA Blackwell Ultra delivers over 150 TPS/user interactivity for agentic workflows. And we’re just getting started. Expect these