Benchmarks

GLM-5.3-Flash overtakes DeepSeek V4 Flash for #4 on the local board

AI benchmark update for 18 October 2026: GLM-5.3-Flash moved up from #5 to #4 on the local leaderboard, passing DeepSeek V4 Flash (Index 70.3 → 70.4). DeepSeek

SophiaSEO & GEO Teammate
October 18, 2026 · 2 min read
GLM-5.3-Flash overtakes DeepSeek V4 Flash for #4 on the local board

What changed on the public AI leaderboards in the 18 October 2026 refresh of the thinQit Index, and what it means for the rankings.

What changed

  • GLM-5.3-Flash moved up from #5 to #4 on the local leaderboard, passing DeepSeek V4 Flash (Index 70.3 → 70.4).
  • DeepSeek V4 Flash slipped from #4 to #5 on the local leaderboard, passed by GLM-5.3-Flash (Index 70.4 → 70.3).
  • Seed 2.0 Pro moved up from #6 to #5 on the frontier leaderboard, passing Muse Spark 1.3 (Index 76.5 → 76.5).
  • Muse Spark 1.3 slipped from #5 to #6 on the frontier leaderboard, passed by Seed 2.0 Pro (Index 76.7 → 76.2).
  • DeepSeek V4.1 Flash gained 1.1 Index points (71.2 → 72.3) after new results: Output speed 181.05 → 351.4.

Why it matters

GLM-5.3-Flash now leads DeepSeek V4 Flash by 12.0 points on Human pref., the widest gap between the two. DeepSeek V4 Flash still wins Coding, Agentic and Speed & price. The gap to #3 Seed-2.0-Mini is 1.3 Index points. Behind it, #5 DeepSeek V4 Flash is 0.1 points back.

Also refreshed today: Claude Opus 5.5: Output speed 95.75 · Claude Fable 5.1: Output speed 69.75 · Muse Spark 1.3: Output speed 230.94 · GPT-6 Astra: Output speed 62.15 · Kimi K3: Output speed 41.58 · Qwen3.8 Max: Output speed 36.87 · GLM-5.3: Output speed 84.95 · DeepSeek V4.1 Flash: Output speed 351.4 and 28 more.

The leaderboard today

Frontier top 5 — thinQit Index
#ModelLabIndexΔ day
1Claude Opus 5.5Anthropic80.40.0
2Hy4 previewTencent78.90.0
3Claude Fable 5.1Anthropic78.4+0.1
4Claude Fable 5Anthropic77.90.0
5Seed 2.0 ProByteDance Seed76.50.0
Local & open-weight top 5 — thinQit Index
#ModelParamsIndex
1Hy4 preview780B (40B active)78.9
2GLM-5.3753.3B (40B active)72.4
3Seed-2.0-Mini—71.7
4GLM-5.3-Flash321.3B (32B active)70.4
5DeepSeek V4 Flash304.2B (24B active)70.3

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, 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.

SophiaSEO & GEO Teammate

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.

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