Grok 4.3 is literally 10x cheaper than GPT-5.5 or Claude for token output costs. It's also shockingly close on benchmarks (or better in some long-horizon agent tests) to the frontier models.
GENERATIVE AI
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Model personality swap creates perfect planner-executor combo
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The models swapped personalities this month. Opus 4.7 got more rigid and precise. GPT-5.5 got more natural and conversational. That's not a bug. That's why this combo works. One model became the perfect planner. The other became the perfect executor. Use them for what
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Opus outlines, GPT-5.5 drafts and executes
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This works beyond coding. Content strategy: use Opus to outline the argument structure. Use GPT-5.5 to draft. Research: use Opus to design the research methodology. Use GPT-5.5 to execute the analysis. Business planning: use Opus to define the framework. Use GPT-5.5 to
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External plans boost GPT-5.5’s confidence and productivity
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Step 3: Let GPT-5.5 run. It will work through the plan methodically. The key insight: GPT-5.5 is more confident when given explicit instructions from an external plan than when it generates its own. It stops second-guessing. It stops being lazy. It builds.
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Codebase analysis and rewrite planning with Claude Opus 4.7
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The exact workflow: Step 1: Open Claude. Select Opus 4.7. Prompt:
"Analyze this codebase. Write a detailed rewrite plan from first principles. Include exact file structure, line limits per file, and architectural decisions. Do not write any code. Plan only." -
Opus 4.7 tight plans enable GPT-5.5 confident execution
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Why this works. Opus 4.7 writes tight, contract-style plans. Exact file counts. Line limits. First-principles architecture. It thinks like a senior engineer scoping a project. GPT-5.5 reads that plan and executes with confidence. It deletes files, rewrites from scratch,
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Opus 4.7 plus GPT-5.5 nearly doubles benchmark scores
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Dan Shipper at Every tested this on their Senior Engineer Benchmark. The scores:
Opus 4.7 alone: low 30s GPT-5.5 alone: low-to-mid 40s Opus 4.7 planning + GPT-5.5 executing: 62.5 For reference, human senior engineers score 80-90. The combo nearly doubled either model's -
AI coding workflow pits Opus 4.7 planner against GPT-5.5 executor
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I tested the highest-performing AI coding workflow of 2026. It doesn't use one model. It uses two competing models against each other. Opus 4.7 plans. GPT-5.5 executes. The results aren't close. (Prompts included)
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Why 1M-Context Models Still Don’t Work Beyond 200K Tokens
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it is endlessly fascinating to me that we still don't have a true 1M-context model it's an unusual case where the infra is far ahead of the science. Claude discontinued 1M+ context bc it didn't really work past ~200k we don't have the right data? training techniques? not sure
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Runway Characters Enables Real-Time Conversational Video Agents at 24fps
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Real-time video agents are here.
— Runway (@runwayml) 4 mai 2026
Today, we’re sharing how we built Runway Characters, allowing you to turn one image into a fully expressive, conversational video agent streaming at 24 frames per second in HD. With just 1.75 seconds of end-to-end latency.
Learn more below. pic.twitter.com/CJqv3Kdl0vReal-time video agents are here. Today, we’re sharing how we built Runway Characters, allowing you to turn one image into a fully expressive, conversational video agent streaming at 24 frames per second in HD. With just 1.75 seconds of end-to-end latency. Learn more below.