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RT @jerryjliu0: We comprehensively benchmarked Opus 4.7 on document understanding. We evaluated it through ParseBench - our comprehensive…
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RT @jerryjliu0: We comprehensively benchmarked Opus 4.7 on document understanding. We evaluated it through ParseBench - our comprehensive…
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"text": "We comprehensively benchmarked Opus 4.7 on document understanding.\n\nWe evaluated it through ParseBench - our comprehensive OCR benchmark for enterprise documents where we evaluate tables, text, charts, and visual grounding.\n\nThe results 🧑🔬: \n- Opus 4.7 is a general improvement over Opus 4.6. It has gotten much better at charts compared to the previous iteration\n- Opus 4.7 is quite good at tables, though not quite as good as Gemini 3 flash \n- Opus 4.7 wins on content faithfulness across all techniques (including ours) \n- Using Opus 4.7 as an OCR solution is expensive at ~7c per page!! For comparison, our agentic mode is 1.25c and cost-effective is ~0.4c by default. \n\nTake a look at these results and more on ParseBench! https://t.co/tYiSOMbd6p",
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"text": "Anthropic says Opus 4.7 hits 80.6% on Document Reasoning — up from 57.1%.\n\nBut \"reasoning about documents\" ≠ \"parsing documents for agents.\"\n\nWe ran it on ParseBench.\n\n→ Charts: 13.5% → 55.8% (+42.3) — huge\n → Formatting: 64.2% → 69.4% (+5.2) \n→ Content: 89.7% → 90.3% (+0.6) \n→ Tables: 86.5% → 87.2% (+0.7) \n→ Layout: 16.5% → 14.0% (-2.5) — regressed\n\nReal chart gains, but at ~1.5¢/page. Enterprise scale? Not yet.\n\nLlamaParse Agentic: 84.9% overall. ~1.2¢/page.\nThe frontier for general document understanding is long. No single model solves it.\n\n→ https://t.co/h7SpuTWYVn",
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