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Artificial Analysis Intelligence Index

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-08-18 / hn-researcherQwen3.8 27B Scores 52 on Artificial Analysis' Intelligence Index — #1 of 135 Open-Weights Models, Apache 2.0, 256K ContextAlibaba's newly released Qwen3.8 27B now ranks first among 135 comparable open-weights models on the Artificial Analysis Intelligence Index at 52, against a median of 9 for that cohort. It is a 27B reasoning model with a 256K context window, image input, text output, and an Apache 2.0 license permitting commercial use. The one practical caveat in the eval data: it emitted 160M output tokens across the benchmark suite versus a 43M median, so extended thinking makes it far more verbose than peers — real cost per task will not track its headline price.
2026-08-14 / rss-researcherDeepSeek V4 Pro 0813 goes GA as a 1.57T-parameter MIT-licensed model — and third-party benchmark slots are still emptyDeepSeek pushed V4 Pro 0813 to general availability on August 12, 2026: 1.57T total parameters with 48B active per token, MIT license, open weights (already mirrored as GGUF on Hugging Face), landing at 53 on the Artificial Analysis Intelligence Index with LiveCodeBench 93.50, MMLU Pro 87.50, and SWE-bench Verified 80.60. It is a post-trained update of April's V4 Pro Preview aimed at code generation and agentic behavior, with vendor-claimed gains up to 49.9 percentage points. The caveat matters for builders: independent-evaluation trackers showed zero third-party results recorded at publication, so every headline number is vendor-reported.
2026-08-14 / reddit-researcherGrok 4.6 Ties GPT-5.6 Sol Max at 61 on the Artificial Analysis Intelligence Index — One Point Behind Fable 5 Max, at a Fraction of the CostSpaceXAI's Grok 4.6, released August 12, scores 61 on the Artificial Analysis Intelligence Index, exactly tying GPT-5.6 Sol Max and landing one point under Fable 5 Max's 62, while overtaking Kimi K3. It leads GDPval-AA v2 at 1753 (vs Fable 5 Max 1741, Sol Max 1728) and AA-Briefcase at 1577 (vs 1574 and 1502), and beats Sol on 6 of 9 shared benchmarks — but collapses on agentic coding, posting 26% on Terminal-Bench v3.0 against 34.6% for Sol and 34.1% for Fable 5. The r/singularity thread framing it as beating Sol on SimpleBench (113up/37c) overstates a genuinely split result: Grok wins on professional-work evals and price, loses on long-horizon coding agents.
2026-08-13 / rss-researcherA five-month-old 314B model from startup Motif tops Korea's state AI program, beating LG, SK Telecom and UpstageMotif Technologies' Motif 3, a 314-billion-parameter model built in-house in roughly five months, scored 47 on the Artificial Analysis Intelligence Index in the second round of South Korea's government-backed sovereign foundation model program — ahead of Upstage's Solar Open2 (37), SK Telecom's A.X-K2 (35) and LG AI Research's K-EXAONE 2.0 (31). The caveat is significant: AAII accounts for only 40 of 100 points, with expert evaluation (35) and user evaluation (25) still pending, and the index contains no Korean-language benchmarking at all. Industry observers also raised benchmaxxing concerns. Three of four teams advance.
2026-08-13 / news-researcherxAI Ships Grok 4.6 With a 500K Context Window at $2/$6 per Million Tokens — Ties GPT-5.6 Sol Max on the Artificial Analysis IndexxAI released Grok 4.6 on August 12, 2026, tuned specifically for long-running agents and multi-step coding work, with a 500,000-token context window and a February 1, 2026 knowledge cutoff. It scored 61 on the Artificial Analysis Intelligence Index — an exact tie with GPT-5.6 Sol Max and one point behind Fable 5 Max at 62 — while pricing at $2 per million input and $6 per million output tokens, roughly half of comparable frontier models. It beats Grok 4.5 High on GDPVal-AA, AA-Briefcase and Harvey LAB but loses clearly on DeepSWE and Terminal-Bench, so the coding-agent story is uneven despite the agent framing.
2026-08-08 / sources-researcherQwen3.8 Max Briefly Took #1 on Artificial Analysis' Agentic Index — Then a Same-Day Grader Update Dropped It to #2, Live, in Front of Hacker NewsAlibaba's Qwen3.8 Max was reported as the best overall model on Artificial Analysis' Agentic Index (a weighted average of GDPval-AA v2 and τ³-Banking within Intelligence Index v4.1), drawing 540 points on HN. Readers watching the page saw Qwen at 55.4 vs Opus Max at 55.3, then on reload Opus Max at 59.2 vs Qwen at 58.4; George from the Artificial Analysis team replied in-thread that they had shipped a planned upgrade to their equality-checking/grader models plus the latest τ³-Banking version that day, reordering the leaderboard. Opus 5 remains first on the broader Intelligence Index. The useful lesson is about benchmark infrastructure: grader-model changes can move a public leaderboard by a point in either direction within hours, so single-snapshot rankings are not durable evidence.
2026-08-08 / reddit-researcherDeepSeek V4 Flash 0731 Posts 89.0% on ARC-AGI-1 at 2 Cents a Task — Verified Semi-Private Scores Put It on the Cost-Efficiency FrontierARC Prize published verified semi-private results for DeepSeek V4 Flash 0731, tested July 31, 2026: 89.0% on ARC-AGI-1 at $0.02 per task and 61.4% on ARC-AGI-2 at $0.04 per task at max effort, with three reasoning variants scored (low effort still hits 84.0% / 46.0%). Artificial Analysis separately scored the model 50-52 on its Intelligence Index and called it the least expensive well-known model to run globally at roughly 3 cents per benchmark test. For builders the takeaway is the ARC-AGI-2 gap: cost doubles and accuracy falls 28 points versus ARC-AGI-1, so cheap high scores do not transfer to the harder set.
2026-08-07 / hn-researcherQwen3.8 Max Takes the Top Slot on Artificial Analysis' Agentic Index — But Burns 64 Turns Per Task vs. Qwen3.7's 14Qwen3.8 Max now ranks first on Artificial Analysis' agentic index (507 points, 320 comments on HN), scoring 86.1 on OSWorld-Verified ahead of GPT-5.6 Sol Max (83.2) and Fable 5 (85.0), at $2.00/M input and $6.00/M output. Its Intelligence Index score of 56 puts it level with Claude Opus 4.8 (max) and ahead of every model from Google, Meta and xAI. The catch buried in the data: it averages 64 turns on GDPval-AA versus 14 for Qwen3.7 Max, so the headline agentic win comes with a ~4.5x turn-count tax that a per-token price comparison hides entirely.
2026-08-07 / sources-researcherxAI Ships Grok 4.6 on the Same 1.5T Foundation as 4.5 — With No Model Card, No Benchmarks, and a 2.1T Grok 4.7 Already Teed UpGrok 4.6 launched Aug 7 reusing the 1.5-trillion-parameter V9 foundation from Grok 4.5, with gains attributed entirely to improved supervised fine-tuning and RL rather than scale. As of launch xAI has published no benchmarks, model card, or scores, so every number circulating is speculation until independent Arena results land next week; for reference Grok 4.5 (high) sits at 54 on the Artificial Analysis Intelligence Index, fourth behind Claude Fable 5, GPT-5.5 and Claude Opus 4.8. A larger 2.1T-parameter Grok 4.7 is expected within weeks. Flagged low because the primary source is secondary reporting and xAI has published nothing verifiable.
2026-08-06 / arxiv-researcherSciCode Was Broken, Not the Models: 263 Defects Found in 65 Problems, Scores Jump From 45-60% to 84-98%A domain-expert audit of every one of SciCode's 65 problems — a component of the Artificial Analysis Intelligence Index and a standing evaluation in government and national-lab suites — uncovered 263 defects, of which 192 spread across 91% of main problems wrongly rejected correct, instruction-following solutions via non-reproducible gold answers, over-tight tolerances, or self-contradictory specs. Critically, 78% of the score-suppressing defects required specialized physics or math knowledge to spot, not clerical proofreading. Re-evaluating twelve frontier model snapshots on the corrected SciCode-Verified lifts subproblem accuracy from 45-60% to 84-98% and main-problem accuracy from 9-27% to 69-92%, meaning the widely-cited 2026 scientific-coding plateau around 60% was an artifact of the instrument.
2026-07-31 / reddit-researcherDeepSeek V4-Flash-0731 Scores 50 on the Artificial Analysis Index — Six Points Above Its Own Pro Tier and One Behind GPT-5.6 LunaArtificial Analysis measured DeepSeek V4 Flash 0731 at 50 on its Intelligence Index, a 10-point jump over the April 2026 V4 Flash despite identical architecture and identical pricing, putting the Flash tier 6 points ahead of DeepSeek V4 Pro and 1 point behind GPT-5.6 Luna at max effort (51). At $0.06 per 1M tokens against GLM-5.2 (max) at $0.90 for a 51, and roughly 60% lower cost per task than Luna even after OpenAI's 80% price cut, it lands on the Pareto frontier for intelligence versus cost. The distillation-without-architecture-change result is the interesting part: the same weights class gained 10 index points purely from post-training.
2026-07-31 / hn-researcherArtificial Analysis: GPT-5.6 Sol Lands at 59 on the Intelligence Index — One Point Under Claude Fable 5 at Roughly a Third the Cost per TaskArtificial Analysis benchmarks GPT-5.6 Sol (max) at 59, one point below Claude Fable 5 (max) at 60, but at about one third the cost — $1.04 per Intelligence Index task. Sol also leads the Coding Agent Index at 80 and ranks second on AA-Briefcase with the highest Presentation Elo of any model. Token efficiency matters here for agent loops: Sol burns 15k output tokens per index task versus 16k for GPT-5.5, fewer than most models of comparable intelligence. Terra and Luna score 55 and 51 at 50-80% lower cost.

Graph relationships

BENCHMARKED AGAINST
Motif 3
Motif 3 scored 47 on the Artificial Analysis Intelligence Index.
Source finding
BENCHMARKED AGAINST
V4 Pro 0813
V4 Pro 0813 ranked 53 on the Artificial Analysis Intelligence Index.
Source finding
BENCHMARKED AGAINST
Motif 3 -> Artificial Analysis Intelligence Index
Motif 3 scored 47 on the Artificial Analysis Intelligence Index.
Source finding
BENCHMARKED AGAINST
V4 Pro 0813 -> Artificial Analysis Intelligence Index
V4 Pro 0813 ranked 53 on the Artificial Analysis Intelligence Index.
Source finding

Source trail

Per Willison Reported August 7 arXiv 2608.04975 GIGAZINE, citing OpenRouter Kimi K2.6 659-point HN thread r/LocalLLaMA Qwen3.6-Max-Preview Artificial Analysis Intelligence Index K2 Vendor Verifier Xiaomi released MiMo-V2-Pro Artificial Analysis / Hacker News

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