AI model
OpenAI's flagship GPT-6 model, rated as the first capable of autonomously exploiting hardened computer systems, offered in several speed and capacity tiers.
Elorian, a Palo Alto startup that raised a $55 million seed round, released Glimpse, a model that crops, zooms and runs code on images while it reasons. Elorian's own evaluations put it ahead of GPT-6 Astra on scientific charts and short video captions.
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Cryptography specialists say they are overwhelmed by requests to validate amateurs' GPT-6 Astra cipher solutions, Nature reports. A claimed solution can be ready by morning, and in Nature's two examples each went to one named person for confirmation.
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Google DeepMind's Gemini 4 Argon scored 97.5% on ARC-AGI-3 at a $4,800 run cost in ARC Prize testing, second to GPT-6 Astra's 99.9%. The score depends on vendor-specific harness features, so it says less about a team's own workload than the headline implies.
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Meta launched Muse Wonder and Muse Wonder Full and says they rival the best models from OpenAI and Anthropic. Both reports rest on Meta's own benchmark figures, so teams choosing a vendor have one more candidate to test on their own work.
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Google is rolling out Gemini 4 Argon to AI Pro subscribers in the Gemini app, where it was Ultra-only. Antigravity's own desktop app and CLI still require Ultra, 9to5Google reported.
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GPT-6-Astra, running in OpenAI's Codex, solved 49 of 50 unpublished theoretical-physics problems on the TheoPhysEval benchmark. The problems are routine research calculations, and the authors say AI still lacks the "taste" for breakthroughs.
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Decomp.dev, the video game decompilation site, is shutting down because its administrator cannot tell human-led projects from AI ones. 404 Media's report relies on the pseudonymous admin's post and does not include a count of AI-assisted projects.
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Artificial Analysis scores Meta's Muse Wonder Full at 56, two points behind Claude Opus 5.5 at 58. Meta's own model card has Full ahead on long-running agentic tasks, so the right pick depends on how closely your workload resembles those tasks.
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Google DeepMind's table puts Gemini 4 Argon ahead of GPT-6 Astra on 14 of 19 benchmarks, with four losses and one tie, The Daily Flare reports. Astra's wins cluster in terminal tests, so coding teams should run their own workloads.
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ProofCouncil solved nine of First Proof's 10 research-math problems in round three, and open-weight Kimi K3 solved none. Mathematicians who avoid frontier models over data-leakage fears have no open-weight option that scored on this exam.
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Google made Gemini 4 Argon widely available and says it ranks #1 on the Vals Index at 68.90%. On the CWE-bench v1 security benchmark it ties two other models at 68%.
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OpenAI's Dots agents are unavailable at launch to Pro subscribers in the EU, the UK and four other European countries. Engadget reports Business Premium customers get them wherever ChatGPT is offered, so the gap sits with Pro.
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Amazon Bedrock now serves OpenAI's GPT-6 Sol and Luna through global cross-Region inference from five Asia-Pacific Regions. GPT-6 Astra is callable only from Singapore, so four of the five source Regions cannot use it.
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OpenAI's cheapest individual plan for a Dot costs $100 a month, five times Meta's $20 Muse Power tier, Engadget reports. Training defaults and regional limits differ too, and those are the settings a rollout owner answers for.
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Anthropic's Claude Sonnet 5.5 resolves 70.6% of Terminal-Bench 4.0 tasks against 66.4% for Opus 5.5, a dev.to post reports. If that gap holds on a team's own tasks, the mid-tier model is the one to test first as the default for terminal agents.
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Epoch AI's InnovationEval credited GPT-5.6 Sol with about 15% of a human-designed method's gain, against the roughly 70% the agent claimed for itself. Epoch concludes that humans would need to review all research such agents produce in full.
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4DCodeBench, a 200-scene benchmark from Stanford's Ziga Kovacic and collaborators, finds the top coding agent scores 0.91 on static metrics but 0.67 on motion. Teams using agents to turn video into simulation code should test the motion on its own.
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SpaceXAI lists Grok 4.7 at $2 and $6 per million tokens against $10 and $50 for GPT-6 Astra and Claude Fable 5.1, and the only per-task figures in the record put a Cursor run at $4.69 against about $9.
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Robocurve's RoboHarm harness put three frontier policies through 300 fixed trials on a pair of $2,999 arms. The published per-trial logs show where a refusal landed and what it cost in model calls.
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GPT-Live-1 costs $0.05 a minute and passes slow requests to a backend model through a delegation event. One early customer reports deleting 23,000 lines of orchestration, about 80 percent of its voice codebase.
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