What changed on the public AI leaderboards in the 31 October 2026 refresh of the thinQit Index, and what it means for the rankings.
What changed
- Mistral Large 4 gained 10.2 Index points (48.3 → 58.5) after new results: LiveBench Coding 60 → 95.4%; LiveBench Agentic 8.8 → 27.5%; LiveBench Reasoning 83.9 → 85.2%.
Why it matters
LiveBench Coding feeds the Coding capability, which carries 25 % of the Index. The gap to #39 Grok 4.7 is 0.0 Index points. Behind it, #41 Kimi K2.7 Code is 0.9 points back.
Also refreshed today: Gemini 4 Carbon: Output speed 87.41 · Claude Opus 5.5: Output speed 97.09 · Claude Fable 5.1: Output speed 71.54 · Gemini 4 Argon: Output speed 79.26 · GPT-6.1 Sol: Output speed 79.61 · Claude Sonnet 5.5: Output speed 134.99 · GPT-6 Astra: Output speed 82.69 · DeepSeek V4.1 Flash: LiveBench Agentic 35.7% and 49 more.
The leaderboard today
| # | Model | Lab | Index | Δ day |
|---|---|---|---|---|
| 1 | Gemini 4 Carbon | 86.6 | 0.0 | |
| 2 | Claude Opus 5.5 | Anthropic | 83.8 | 0.0 |
| 3 | Claude Fable 5.1 | Anthropic | 82.8 | 0.0 |
| 4 | Muse Wonder Full | Meta | 79.4 | 0.0 |
| 5 | Gemini 4 Argon | 79.2 | 0.0 |
| # | Model | Params | Index |
|---|---|---|---|
| 1 | Hy4 preview | 780B (40B active) | 78.9 |
| 2 | Seed-2.0-Mini | — | 71.7 |
| 3 | GLM-5.3 | 753.3B (40B active) | 70.9 |
| 4 | DeepSeek V4 Flash | 304.2B (24B active) | 69.7 |
| 5 | Seed-2.0-Lite | — | 69.5 |
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, LMArena, LLM-Stats, LiveBench, 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.
