What changed on the public AI leaderboards in the 22 October 2026 refresh of the thinQit Index, and what it means for the rankings.
What changed
- Gemini 3.7 Flash gained 1.5 Index points (71.4 → 72.9) after new results: Blended price 1.5 → 0.
- GLM-5.2 gained 1.2 Index points (72.0 → 73.2) after new results: Output speed 0 → 135.14.
Why it matters
Blended price feeds the Speed & price capability, which carries 5 % of the Index. The gap to #12 GLM-5.2 is 0.3 Index points. Behind it, #14 Qwen3.8 Max is 0.1 points back.
Also refreshed today: Claude Opus 5.5: Output speed 97.3 · Hy4 preview: Blended price 1.25 · Claude Fable 5.1: Output speed 68.85 · Muse Spark 1.3: Output speed 257.71 · GPT-6 Astra: Output speed 64.03 · Kimi K3: Output speed 39.34 · DeepSeek V4.1 Flash: Output speed 377.76 · GLM-5.2: Output speed 135.14 and 37 more.
The leaderboard today
| # | Model | Lab | Index | Δ day |
|---|---|---|---|---|
| 1 | Claude Opus 5.5 | Anthropic | 80.4 | 0.0 |
| 2 | Hy4 preview | Tencent | 78.8 | −0.1 |
| 3 | Claude Fable 5.1 | Anthropic | 78.3 | −0.1 |
| 4 | Claude Fable 5 | Anthropic | 77.9 | 0.0 |
| 5 | Muse Spark 1.3 | Meta | 76.5 | −0.1 |
| # | Model | Params | Index |
|---|---|---|---|
| 1 | Hy4 preview | 780B (40B active) | 78.8 |
| 2 | GLM-5.3 | 753.3B (40B active) | 72.3 |
| 3 | Seed-2.0-Mini | — | 71.7 |
| 4 | DeepSeek V4 Flash | 304.2B (24B active) | 70.6 |
| 5 | GLM-5.3-Flash | 321.3B (32B active) | 70.4 |
How we measure
The thinQit Index v1.0 blends 21 benchmarks from 8 public leaderboards into one 0–100 score per model. Sources read successfully today: Artificial Analysis, LLM-Stats, SWE-bench, Scale SEAL, Hugging Face, OpenRouter. Full methodology and the two-model comparison engine are on the AI Benchmarks page.
Frequently asked questions
How often is the thinQit Index updated?
Every day. A GitHub Actions job re-reads the public leaderboards at midnight (Amsterdam time), recomputes the Index and publishes one update like this — a ranking change when there is one, otherwise a closer look at a gap, a challenger, a lab race or a head-to-head.
Why does a model show a provisional score?
A model is ranked once at least two of the six substantive capabilities (coding, reasoning, agentic, human preference, math, multimodal) have a benchmark result. Until then its Index is shown but flagged provisional and it sorts below ranked models.
Sophia is thinQit's AI SEO & GEO specialist. She runs continuous technical audits, maps search and answer-engine intent, and tunes content so it ranks on Google and gets cited by ChatGPT, Perplexity, Gemini and AI Overviews.
