Claude Opus 5.5 and GPT-6 Astra are dominating the latest benchmarks

GPT-6 Astra and Claude Opus 5.5 lead the Terminal-Bench-Science benchmark by roughly 20 points over Fable 5.1, with the strongest model outside those two labs, Qwen3.8 Max, at just 12%, according to the latest benchmark numbers. Claude Opus 5.5 scores 62% at "xhigh" reasoning effort but dips to 59% at "max," and leads SimpleBench at 88.4% while costing roughly 60% less than Fable 5.1. Xiaomi's MIT-licensed MiMo-V2.6-Pro scores 46 on the AA index at $0.13 per task versus GPT-5.6 Sol's 47 at $1.99.

Claude Opus 5.5 and GPT-6 Astra are dominating the latest benchmarks The latest numbers from Terminal-Bench-Science show a massive gap between the top tier and everyone else. GPT-6 Astra and Claude https://promptcube3.com/en/tags/claude/ Opus 5.5 are leading Fable 5.1 by roughly 20 points. To put that in perspective, the strongest model outside those two labs, Qwen3.8 Max, is sitting at just 12%. It is an incredible time to be building with these tools because the performance ceiling is just skyrocketing. How does Claude Opus 5.5 handle reasoning effort? The scaling of reasoning effort on Terminal-Bench-Science is a bit surprising. Opus 5.5 jumps from 24% at "low effort" up to 62% at "xhigh," but then it actually dips to 59% when set to "max." If you are tuning your prompts, avoid the "max" setting; it imposes a minimum reasoning budget that seems to degrade the output slightly. On the vision side, it is currently ranked as Anthropic’s strongest vision model, beating Fable 5 and GPT-6 Sol, though it still trails GPT-6 Astra. The best part is the efficiency—it is roughly 60% cheaper than Fable 5.1 while leading SimpleBench with an 88.4% score. What is the current state of the GPT-6 family? The different GPT-6 variants are carving out very specific niches: - Astra: This is the heavy hitter for reviews and audits. It reportedly beat NetHack on its third attempt and maintains an 82.5% win rate in DOOM agent matches. - Luna Max : The efficiency play. It hit 24 in Code Arena WebDev with a score of 1593 which is +74 over GPT-5.6 Luna at a blended cost of about $0.40/Mtok. - Sol: The speed king, though it loses to Luna on the wins-per-dollar metric. How do the latest Flash and Open-Weight models compare? Gemini https://promptcube3.com/en/tags/gemini/ 3.8 Flash is putting up some wild numbers, hitting 291 tok/s with a 1M context window. It scored 89.2% on ARC-AGI v2 at $0.40 per task and 98.5% on v1. Interestingly, on v3, it hits 10.4% with the standard harness but jumps to 35% using the provider harness. Then there is the Xiaomi MiMo-V2.6-Pro. It is released under the MIT license, is omni-modal with 1M context, and scores 46 on the AA index. For comparison, GPT-5.6 Sol is at 47. The price difference is where Xiaomi wins—it costs $0.13 compared to $1.99 per task. It is also worth noting that the $200 Claude Code https://promptcube3.com/en/tags/claude%20code/ plan is receiving a lot of praise right now, with a growing consensus that it is officially beating Codex. Whether you are optimizing for raw power with Astra or cost-efficiency with MiMo, there is a perfect tool for every single use case right now. Next Deepfake Detection Fails Without Cross-Generator Generalization → https://promptcube3.com/en/threads/9585/ All Replies （1） Want a live back-and-forth? Join the global AI chat room https://promptcube3.com/en/chat/ — login to talk. That 20 point gap is wild. I'm seeing a huge jump in complex logic tasks with Opus 5.5 compared to my old setup.