AI model comparison — quality, price and open source

Data as of 2026-07-01 · automated research (Artificial Analysis, LMArena, official pricing) — verify before deciding.

📈 Zendoric Quality over time (frontier makers)

Quality index (0-100) of the top makers (their best model), last 24 months. Dashed line = quality estimated from the AA Index (labs without SWE-bench-Pro). Updated daily.

📈 AA Index over time (frontier makers)

AA Index (Artificial Analysis Intelligence Index, 0-100) of the top makers (their best model), last 24 months. It is a broader composite index (reasoning, science, code, maths) than ours. The historical series is reconstructed by anchoring each maker's trajectory to its current AA. Updated daily.

🛡️ Cybersecurity over time (frontier makers)

Cybersecurity index (0-100) of each maker's best model, last 24 months. Metric: EXPERT cyber tasks under a hard «unguided pass@1» protocol (no hints, one attempt; vuln-research and realistic exploitation). We pick it because it is NOT saturated — the top is around 71, not 100, so it discriminates and shows headroom (we drop Cybench «pass@k», where the frontier already scores ~100%). Sources: UK AISI (GPT-5.5 71.4% vs Anthropic preview 68.6%), NIST-CAISI, CVE-Bench. High confidence only for OpenAI/Anthropic (measured by AISI); the rest imputed by proximity → the whole series is marked «est.». We frame it as capability and RISK to govern, not an offensive ranking. Updated daily.

💰 Zendoric Quality vs cost

Flagship models of the top makers by quality (a maker may have several, e.g. Anthropic: Opus 4.8 and Fable 5). HIGHER = more quality; LEFT = cheaper (log axis). Hollow dot = quality estimated (AA Index). Colour by maker.

💰 AA Index vs cost

Same format as the quality/cost chart, but the vertical axis is the AA Index. HIGHER = more capability; LEFT = cheaper (log axis). Hollow dot = estimated AA (Terminal-Bench/SWE-Pro). Colour by maker.

🏆 Zendoric Quality (SW dev + arena + agentic)

Quality = equal-thirds average of SWE-bench-Pro (SW development) + LMArena (human preference) + Terminal-Bench (agentic capability), the three with reliable sources (Zendoric Quality); if one is missing its weight is shared among those present (at least two; otherwise «—»). LiveCodeBench and GPQA are shown for reference (indicative, may be incomplete) but are NOT in the index; ARC-AGI-2 (arcprize.org) tracks AGI progress: models score VERY low → still far from AGI. %, except LMArena (Elo).

💵 Economics (USD / 1M tokens)

Claude Sonnet 5: scheduled price increase (same model) — reduced pricing until Aug 31, 2026 and standard pricing from Sep 1, 2026.

🔓 Open source & type

🖥️ Open source you can self-host

Small/medium models you can run on your own machine (laptop/PC/Mac). Quality = Artificial Analysis Intelligence Index (0-100; output quality), the measure with best coverage of small open models (LMArena does not list sub-32B). Memory estimated at 4-bit (Q4) and 8-bit (Q8) quantization; on Apple Silicon it is UNIFIED memory (RAM=VRAM).

🗄️ Large open source (server / multi-GPU)

Powerful open models that need a server or multiple GPUs. Quality = LMArena Elo (human preference over output, source lmarena.ai), which does cover large models. For MoE, memory counts total parameters (all experts are loaded). Memory estimated at 4-bit (Q4) and 8-bit (Q8) quantization; on Apple Silicon it is UNIFIED memory (RAM=VRAM).