Benchmark 100 AI Models — Real Results 2026 (LLM Benchmark Report, PDF)

📊 LLM benchmark report: 64 AI benchmarks with real measured scores, reproducible data, 2026 edition — not marketing numbers.

Benchmark 100 Modele AI — Rezultate Reale 2026

Real measured scores. Not vendor claims. 3,438 tasks evaluated over 77+ hours of live inference.

This is Edition 1.0 of an independent, reproducible benchmark report covering the 100-benchmark AI suite. Every score in this report was produced by running actual frontier open-weight models (deepseek-v4-flash, z-ai/glm-5.2) through a local inference gateway — temperature 0, official datasets, exact-match / unit-test scoring. No estimates, no interpolation.

What you get

Full results table — all 64 completed benchmarks: model, group, score, sample size, run date.

3 analysis sections — Top 10 deep dive, the surprises marketing doesn't tell you, value-per-dollar use-case guidance.

Group averages — knowledge / reasoning / math / code / multilingual / safety / instruction.

Complete methodology — reproduce every number yourself.

Roadmap — the remaining 36 benchmarks of the suite (GPQA-Main, HLE, MathVista, SWE-bench-lite, GAIA, BFCL-v3, Arena-Hard and more).

Machine-readable dataset — CSV with all 64 scores bundled.

Key findings

IFEval 100.0 — instruction following is flawless on all 100 items

Winogrande 98.0, PIQA 94.0, CMMLU 86.0, TruthfulQA 84.0 — knowledge strong

Reasoning average only 29.8 — DROP, tracking and mapping tasks score 0

Math weak spot: GSM8K 47.0, AIME-2024 36.7, MBPP 5.0

Multilingual fragile: XCOPA 5–10, XStoryCloze 5.0 vs XWinograd-zh 95.0

Edition 2.0 (remaining 36 benchmarks) ships free to all Edition 1.0 buyers.

29 EUR — the raw inference for this suite costs 150–250 USD to reproduce.