tag: benchmarks
articles: 2 · beats: 2
latest: October 17, 2026
---
Benchmarks
2 Crashtech articles on Benchmarks, spanning Breakthroughs and Development Best Practices, published between July 2026 and October 2026. Every piece is full-text HTML with sources, structured data and an authored FAQ.
They span Breakthroughs (1), Development Best Practices (1). Breakthroughs Development Best Practices
Can AI Labs Sit an Exam Without Seeing the Questions?
A confidential-computing pilot separates model weights from evaluation prompts, while leaving the harder question of test validity open.
JetBrains Built Its Own AI Coding Benchmark Because It Doesn't Trust Anyone Else's
JetBrains released a 105-task, open Kotlin coding benchmark on July 8, 2026 — and Claude Code beat JetBrains' own Junie agent by 3.81 points at launch.
Questions we answer about Benchmarks
- What does double-blind mean in this AI evaluation pilot?
- Does confidential computing prove an AI benchmark is fair?
- Can a double-blind test eliminate benchmark contamination?
- What is the Kotlin Benchmark, and why did JetBrains release it?
- How many tasks are in the Kotlin Benchmark, and where do they come from?
- Which AI coding agent topped the first Kotlin Benchmark leaderboard?
- Does a high Kotlin Benchmark score guarantee an agent will work on my codebase?
- What comes next for the Kotlin Benchmark?
Frequently asked questions
What does Crashtech publish about Benchmarks?
2 articles tagged Benchmarks, the most recent published October 17, 2026. They span Breakthroughs (1), Development Best Practices (1). Each carries numbered sources, an authored FAQ and full structured data.
What questions about Benchmarks does Crashtech answer directly?
8 questions have a dedicated answer page under this tag, including “What does double-blind mean in this AI evaluation pilot?”. Each answer is authored prose from the article it belongs to, not a generated summary.
Can AI assistants read Crashtech's Benchmarks coverage?
Yes. Crashtech serves full static HTML to every crawler, allows all major AI user agents in robots.txt, and publishes an llms.txt manifest plus a full-text corpus, so assistants can retrieve and cite these articles directly.