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
AI
-
Token efficiency: GPT-5.5 vs Claude Opus 4.7 cost and speed
By
–
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
-
GPT-5.5 outperforms Claude Opus 4.7 by 13 points on terminal benchmarks
By
–
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
By
–
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
-
LLM 0.32a0 Released: Major Refactor for Reasoning Models
By
–
I released LLM 0.32a0 this morning, a major backwards-compatible refactor of my LLM Python library and CLI tool for working with language models – the new changes should help LLM work better with reasoning models and other new frontier capabilities
-
Claude Opus 4.7 leads GPT-5.5 on 6 of 10 benchmarks by category
By
–
On the 10 benchmarks where both OpenAI and Anthropic report scores, here's the split: Claude Opus 4.7 leads on 6. GPT-5.5 leads on 4. But the leads aren't random. They cluster by category. And that changes what "winning" means entirely.
-
GPT-5.5 vs Claude Opus 4.7: The real benchmark story
By
–
GPT-5.5 shipped 7 days after Claude Opus 4.7. Everyone picked a winner based on headlines. I looked at every benchmark both labs published. The real story isn't what most people are reporting:
-
Databricks Agents Automate Security Workflows at RSAC2026
By
–
At #RSAC2026, Databricks co-founder and CEO @alighodsi showed how agents can take on security workflows that are manual today and often require hundreds of people.
— Databricks (@databricks) 29 avril 2026
With data in an open security lakehouse, agents can normalize and organize data, monitor and fix pipelines, write… pic.twitter.com/WIdM8R6NSfAt #RSAC2026, Databricks co-founder and CEO @alighodsi showed how agents can take on security workflows that are manual today and often require hundreds of people. With data in an open security lakehouse, agents can normalize and organize data, monitor and fix pipelines, write
-
Industrial AI Professionals Gather at April Conferences
By
–
April's 10 conferences across 7 countries create intensive month for industrial AI professionals before virtual options resume.