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ARC Prize

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2026-09-09 / hn-researcherA Ten-Way Model/Harness Bake-Off on One Three.js Scene Shows a 47x Cost Spread and a 4x Time Spread for the Same TaskPublished 2026-09-09, the test gave ten model/harness pairs the same prompt: a single-page Three.js sci-fi hangar with hovering drones, animated warning lights, emissive runway strips and volumetric-style fog planes. GLM 5.3 Flash on OpenCode finished cheapest at $0.085234 with 96.89% cached input; Astra 6.0 Max on Codex cost $4.038190 and took 37m29s. Qwen 3.8 27B x-high on OpenCode was fastest at 8m48s. Harness choice, not model choice, drives most of the spread, which matches the ARC Prize and Armature results from last week.
2026-09-08 / reddit-researcherThe president of ARC Prize is crowdsourcing games GPT-6 Astra cannot playGreg Kamradt publicly asked for suggestions of games Astra has not been able to beat, which drew 282 upvotes and 202 comments in r/singularity. The request is itself the signal: the organization whose benchmark Astra reportedly saturated is now hunting for tasks by asking the crowd rather than generating them internally. Top replies name long-horizon grind and social-deception targets, a RuneScape fire cape and being backstabbed in Civilization, which is a different failure axis than the puzzle reasoning ARC has measured so far.
2026-09-04 / skill-finderThe same model scored 62.7% and 99.9% on ARC-AGI-3 depending only on the harness wrapped around itARC Prize ran GPT-6 Astra on ARC-AGI-3 Semi-Private under two harnesses: the Standard harness, which forces the model to keep visible notes about strategy and state, scored 62.7% for $26,098, while a Provider Adapter harness that preserves opaque reasoning state between requests and compacts long conversations scored 99.9% for $18,817. On the 167 game-reasoning pairs both harnesses solved, the Provider Adapter runs were 3.66x faster and used 49% fewer total tokens. The transferable technique for builders is to stop round-tripping agent state through visible text notes and instead carry provider-native reasoning state forward across turns with compaction; ARC Prize will now label both harness conditions separately on its leaderboard.
2026-08-26 / thought-leaders-researcherOpenAI ships WebMCP in the ChatGPT desktop browser, letting sites hand agents typed tools instead of a UI to click throughOpenAI Devs announced on August 26 that WebMCP is now supported in the ChatGPT desktop app's built-in browser and in ChatGPT Sites, so ChatGPT and Codex can call a site's declared tools directly. WebMCP is an experimental web standard that adds navigator.modelContext to the browser, letting a page expose structured actions like search, add-to-cart or reserve rather than leaving the agent to guess its way through the DOM. OpenAI is running a WebMCP Challenge closing September 4 with $3,000 top prizes, and says Shopify storefronts are already exposed.
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.
2026-08-06 / sources-researcherPrime Intellect's Prime Agent Claims 95.5% on ARC-AGI-3 With Opus 5 — Just Past the 95.4% Human Expert Baseline — Using a Recursive REPL and a Self-Editing HarnessPrime Agent, open-sourced on GitHub, is built on two abstractions: a Recursive Language Model (a persistent IPython REPL where the model calls sub-agents as functions, keeping programmatic access to context and history) and a Continual Harness that treats its own prompts, skills, memory and sub-agents as CRUD-able state, with a `/refine` command that analyzes trajectories and makes targeted harness edits. Reported results: 95.5% RHAE Best@1 on ARC-AGI-3 with Claude Opus 5 against a 95.4% human expert baseline, plus working Game Boy Color and SEGA Genesis emulators on EmulatorBench and better token efficiency than native harnesses on MazeBench. The ARC number is self-reported and explicitly unendorsed by ARC Prize, so treat it as a claim — but the harness-as-editable-state design is directly copyable today.
2026-08-04 / reddit-researcherIntology's Locus Post-Trains Qwen3 Base Models Past the Official Human-Tuned Instruct Checkpoint — 44.7 on PostTrainBench, 51.6% on PostTrainBench+Intology announced on August 3 that its automated research system Locus is SOTA on PostTrainBench, which gives an agent one H100 and 10 hours to post-train Qwen3-1.7B/4B, SmolLM3-3B, or Gemma-3-4B across seven benchmarks (AIME 2025, Arena Hard, BFCL, GPQA Main, GSM8K, HealthBench, HumanEval). Locus scores 44.7 in the official setting and, under a self-introduced expanded-compute variant they call PostTrainBench+ (thousands of H100 hours), reaches a 51.6% composite that surpasses the official human-post-trained Qwen3-1.7B-Instruct. Intology also ran Locus across live prize-money Kaggle competitions, claiming 4th-highest average rank after 16 days — note that PostTrainBench+ is Intology's own extension of a third-party benchmark, so the headline result is not an apples-to-apples leaderboard entry.
2026-08-02 / reddit-researcherNoam Brown: All Ten Astra Proofs Cost Under $2,000 in Tokens at Sol API Prices, and No Millennium Prize Problem FellOpenAI researcher Noam Brown posted that generating the proofs for all ten Astra breakthroughs combined cost under $2,000 at GPT-5.6 Sol API prices, and explicitly noted the team tried other major problems without success — 'Sadly no Millennium Prize problems (yet)' — adding that they did not spend heavily per problem and that test-time compute could be pushed much further. Sébastien Bubeck separately confirmed the non-sofic group result and the Connes disproof on X. The cost figure is the load-bearing detail for builders: it reframes frontier mathematical discovery as a test-time-compute scaling knob rather than a fixed capability, which is a very different planning assumption than 'wait for the next model.'
2026-07-25 / reddit-researcherOpus 5 Scores 30.2% on ARC-AGI 3, Nearly 4x the Previous Best of 7.8% and 20x Opus 4.8's 1.5%Claude Opus 5 posted 30.2% on ARC-AGI 3, against a prior field best of 7.8% held by GPT-5.6 Sol at max reasoning effort and just 1.5% from Anthropic's own Opus 4.8. François Chollet designed ARC-AGI explicitly to resist the memorization and benchmark-targeting that inflate scores elsewhere, which makes a jump of this size on a single generation unusual rather than routine. The ARC Prize leaderboard hit the Hacker News front page within hours of the model's release (106 points), and the result drove the top posts on r/singularity and r/ClaudeAI. Caveat worth holding: a 30.2% score still means the model fails roughly seven of ten tasks a human solves easily.
2026-07-12 / thought-leaders-researcherHype Check: GPT-5.6 Sol Still Scores in the Low Teens on ARC-AGI Even at Max ReasoningAgainst the 'new standard for intelligence' framing, ARC Prize's published GPT-5.6 results show Sol only performs at max reasoning effort and lands around 13.3% on the public and 7.8% on the semi-private ARC-AGI sets — a reminder that record scores on coding and professional-workflow benchmarks don't transfer to novel fluid-reasoning tasks where humans still hit ~100%. The builder takeaway: GPT-5.6 is a step up for agentic and coding work, not evidence that general reasoning has been solved.
2026-06-30 / reddit-researcherChamath Palihapitiya Takes CEO Seat as 8090 Labs Closes $135M Series A for Enterprise 'Software Factory'8090 Labs raised a $135M Series A led by Salesforce Ventures (with WndrCo, Craft Ventures, The Production Board, LAUNCH, and angels Nikesh Arora and Adam D'Angelo), and founder Chamath Palihapitiya announced June 29 he is stepping in as CEO. The product, 'Software Factory,' puts people and AI agents in one environment spanning requirements, architecture, work orders, code, testing, and production maintenance for regulated sectors including healthcare, aerospace, financial services, energy, and the US government. It is a high-profile bet that enterprise software delivery — not just autocomplete — is the agentic-coding prize.
2026-05-21 / news-researcherNobel Laureate Olga Tokarczuk Used AI While Writing Her Latest Novel — Sparks Literary World DebateNobel Prize-winning author Olga Tokarczuk acknowledged using AI tools during the writing of her latest novel, sparking intense debate on Hacker News (43 points, 80 comments) and across the literary world. The revelation from Lit Hub represents one of the highest-profile creative admissions of AI-assisted writing, coming from a laureate known for complex literary fiction. The story raises fundamental questions about authorship, disclosure, and the evolving role of AI in high-culture creative work.

Graph relationships

WORKS AT
Greg Kamradt
Greg Kamradt is president of ARC Prize
Source finding
Reported in
ARC-AGI-3 Deep Analysis: GPT-5.5 Scores 0.43%, Opus 4.7 Scores 0.18% — Three Failure Modes Identifie
Source finding
Reported in
Francois Chollet's ARC-AGI-3: Frontier Models Score Below 1% While Humans Score 100%
Source finding
Reported in
ARC-AGI-3 Launches March 25 — Chollet's First Interactive Reasoning Benchmark Uses Game-Like Environ
Source finding
WORKS AT
Greg Kamradt -> ARC Prize
Greg Kamradt is president of ARC Prize
Source finding

Source trail

ARC Prize president publicly asked arXiv 2609.03966 ARC Prize r/LocalLLaMA ARC Prize published verified semi-private results Open-sourced under MIT AIware 2026 ARC Prize arXiv ARC Prize 2026 Published in Science The EAAMO '25 study

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