IMO DeepSeek v4 demonstrated utter confidence and competence by not benchmaxxing, not focusing on some BS final run cost, not even spending inference-optimal compute. just showed up, demonstrated SOTA long context efficiency techniques (CSA, HCA, mHC, flash at 8% cost of pro,
TECHNOLOGY
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Professional comparison of Claude and GPT-5.5 capabilities
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The definitive ranking doesn't exist. Here's what does: → Complex reasoning, code review, multi-file refactoring: Claude Opus 4.7
→ Agentic execution, terminal workflows, tool orchestration: GPT-5.5
→ Interactive speed: Claude
→ Cost at scale: GPT-5.5 The professionals -
Claude wins 7 tests but GPT-5.5 leads in OpenAI’s table
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Tom's Guide ran 7 head-to-head tests. Claude won all 7. OpenAI's own benchmark table shows GPT-5.5 leading on 14 categories. But that table includes tests where only OpenAI published a Claude score. Anthropic's own numbers tell a different story on several of those. The
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Token efficiency: GPT-5.5 vs Claude Opus 4.7 cost and speed
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Token efficiency is where things get interesting. GPT-5.5 uses 72% fewer output tokens than Opus 4.7 on the same coding tasks. Fewer tokens means lower cost per task, even though GPT-5.5 costs $30/M output vs Claude's $25/M. But Claude's time-to-first-token is roughly 0.5s vs
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GPT-5.5 outperforms Claude Opus 4.7 by 13 points on terminal benchmarks
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Long-running agentic execution: GPT-5.5
→ Terminal-Bench 2.0: 82.7% → Claude Opus 4.7: 69.4% That's a 13-point gap. Not noise.
→ OSWorld-Verified: 78.7% vs 78.0% → BrowseComp → CyberGym When the task requires driving a terminal, recovering from errors, and -
Claude Opus 4.7 dominates reasoning and code benchmarks
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Deep reasoning and code precision: Claude Opus 4.7 → SWE-Bench Pro: 64.3% → GPT-5.5: 58.6% → MCP Atlas: 79.1% → GPT-5.5: 75.3% → GPQA Diamond, HLE (with and without tools), FinanceAgent v1.1: all Opus 4.7 When the task requires architectural thinking
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AI-Powered 3D Skin Scanning Delivers Precision Medical Insights
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Next-Gen #3D Skin Scanning Powered by #AI Delivers Precision Insights
— Ronald van Loon (@Ronald_vanLoon) 29 avril 2026
by @MarchUnofficial#EmergingTech #Technology #Innovation #Tech #TechForGood pic.twitter.com/BvUDlt0IiNNext-Gen #3D Skin Scanning Powered by #AI Delivers Precision Insights
by @MarchUnofficial #EmergingTech #Technology #Innovation #Tech #TechForGood -
Pixtral Scaled-Up Model: Tradition Over Modern AI Approaches
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Reject modernity, embrace tradition (it's a scaled-up Pixtral)
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iPod Nano 7th Gen: Perfect AI-First Device Design
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If I were building an AI-first device, I’d look no further than the iPod nano 7th gen. This thing was perfect. Thin as a headphone jack. Distraction-free screen. Microphone and Bluetooth.
Years ahead of its time. -
Iterative Material Design Process and Composition Analysis
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Why not more frequently? The process for designing new materials can take many iterative learning cycles, where materials’ compositions are analysed, and resulting effects are closely scrutinised.