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● Live scorecard · Graded June 2026

Was Aschenbrenner
Right?

In June 2024, Situational Awareness predicted AGI by 2027. Two years in, we grade every prediction against reality — what's on track, what's wrong, and what's still open.

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Primary Target
Estimated time to AGI (2027 baseline)
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Days
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Hours
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Minutes
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Seconds

Target: January 1, 2027 · Based on Aschenbrenner's "Counting the OOMs" analysis · Not a precise prediction — a focal point for tracking

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The AGI Test 🎯
What's your AGI type?
When do you think AGI arrives? Pick one — get your archetype and see where you land vs Musk, Aschenbrenner & Metaculus.
2019
GPT-2 — Preschooler level
Could barely string together coherent paragraphs. The baseline that showed language models had potential.
✓ Reached
2023
GPT-4 — Smart high schooler
Aces AP exams, writes sophisticated code, reasons through competition math. Benchmarks rapidly saturated.
✓ Reached
2024
PhD-level benchmarks cracked
GPQA (expert PhD questions) being approached. Claude 3 Opus at ~60% vs 80% for in-domain PhDs.
✓ In progress
2025–26
Outpace college graduates
Models able to perform at the level of a skilled recent grad across most professional tasks. Agent capabilities mature.
⟳ Approaching
2027
AGI — AI researcher level
Models capable of doing the work of an AI researcher/engineer. Could automate AI research itself, triggering intelligence explosion.
⟳ Forecast
2027–29
The Project begins
USG/national security involvement. Government AGI project launches. No startup handles superintelligence alone.
◌ Future
2029–30
Intelligence explosion
Hundreds of millions of AGIs automating AI research. A decade of progress compressed into 1 year.
◌ Forecast
2030s
Superintelligence
Vastly superhuman AI systems. Decisive economic and military advantage. The free world's survival at stake.
◌ Forecast
2030s
Trillion-dollar clusters
US electricity production grows tens of percent. Hundreds of millions of GPUs. Industrial mobilization unlike anything since WWII.
◌ Forecast
OOM Tracker — Effective Compute Scaleup
Orders of magnitude vs GPT-2 baseline
"With each OOM of effective compute, models predictably, reliably get better. If we can count the OOMs, we can extrapolate capability improvements."
— Leopold Aschenbrenner, Situational Awareness (2024)
Raw compute
~2 OOMs/yr
Algorithmic efficiency
~0.5 OOMs/yr
Unhobbling gains
~1 OOM total
GPT-2 → GPT-4 total
~5 OOMs
GPT-4 → 2027 (proj.)
+5 OOMs

Source: Epoch AI public estimates + Aschenbrenner analysis. Dashed bar = projection.

Frontier Labs — Status Overview
Best available public data · Updated June 2026
OpenAI
🇺🇸 USA
Flagship modelGPT-5.5 / 5.5 Pro
Annualized revenue$25B+ (est.)
NotableLeads FrontierMath T4
Release cadence~6 weeks/flagship
Anthropic
🇺🇸 USA
Flagship modelClaude Fable 5 (Mythos)
Annualized revenue~$19B (est.)
NotableNew tier above Opus
StanceSafeguarded frontier
Google DeepMind
🇺🇸 USA
Flagship modelGemini 3.1 Pro / 3.5
NotableGemini Spark agent
AdvantageTPU + multimodal lead
Context window2M tokens native
Chinese Labs (est.)
🇨🇳 China
Key playersDeepSeek, Qwen, MiniMax
Flagship modelsDeepSeek V4, Qwen 3.7 Max
StrategyOpen-weight + low cost
Gap vs frontier~3–6 months (est.)

The Scorecard — Every Prediction vs Reality

Source: Situational Awareness (June 2024) · Graded June 2026 · Last updated: July 12, 2026 · Tap any row for evidence & flip conditions
Target Prediction Reality check (2026) Verdict
2025/26 Models outpace college graduates across knowledge work Frontier models at ~83% on knowledge-work benchmarks; agent products in production ✓ On track▶

Evidence ~83% on GDPval-style knowledge work and ~80% on SWE-Bench Pro; agent products in production. Drop-in reliability without supervision still lags the benchmarks.

Flips if Capability plateaus below skilled-graduate level, or production agent adoption stalls on reliability.

Sources GDPval (OpenAI) · SWE-bench

Full verdict: Can AI replace knowledge workers? →

~0.5 OOM/yr Compute + algorithmic scaling continues at trend One-year retrospectives find the pace roughly supported by evidence ✓ Holding▶

Evidence Effective compute has roughly held the ~0.5 OOM/yr pace; gains increasingly come from reasoning, tools and agents (unhobbling), not just raw scale.

Flips if A sustained multi-year drop below ~0.5 OOM/yr — most plausibly via a capex pullback.

Sources Epoch AI — Trends in AI

Full verdict: Is AI compute still scaling? →

$500B/yr Massive AI capex acceleration Investment exceeding projections; accelerating faster than forecast ✓ Exceeded▶

Evidence Investment exceeded the essay's projections — his most vindicated call. The caveat: revenue lags the spend, which is the bear case to watch.

Watch The revenue-vs-capex gap — a funding pullback would slow the compute trend for financial reasons.

Sources Epoch AI — Finances of AI

Full verdict: Did AI capex hit trillion-dollar scale? →

— Open-source fades; proprietary algorithms create a durable US moat DeepSeek V4 / Qwen open-weight models within 3–6 months of frontier ✗ Wrong▶

Evidence DeepSeek and Qwen open-weight models sit within ~3–6 months of the frontier at a fraction of the cost — the opposite of fading.

Flips back if The frontier pulls a multi-year lead via advances that don't diffuse. No sign of that yet.

Sources Epoch AI

Full verdict: Did open-source AI fade? →

2027 AGI: models do the work of an AI researcher/engineer Agentic coding strong (~80% SWE-Bench Pro) but autonomous research unconfirmed ⟳ Open▶

Evidence Agentic coding is strong (~80% SWE-Bench Pro) but no system has autonomously conducted AI research end-to-end — the bar that defines this claim.

Resolves By January 1, 2028. Fulfilled if autonomous AI research is demonstrated; Wrong if the deadline passes without it.

Full verdict: Will AGI arrive by 2027? →

2027/28 US government launches formal AGI project National-security involvement growing; no formal Project announced ⟳ Open▶

Evidence National-security involvement is growing (export controls, lab security requirements, defense interest) but no centralized, Manhattan-Project-style effort exists.

Resolves By 2027/28. The open-source verdict weakens its premise: diffused capability undercuts the case for a single Project.

Full verdict: Will the US government build AGI? →

2027–29 Intelligence explosion: decade of progress in 1 year Too early to grade ◌ Pending▶

Why pending Its trigger — AI autonomously doing AI research — hasn't been demonstrated, and the 2027–29 window hasn't arrived. Not enough evidence to grade either way.

Full analysis: Will there be an intelligence explosion? →

2030s Superintelligence; decisive geopolitical advantage Too early to grade ◌ Pending▶

Why pending Downstream of AGI and an intelligence explosion, neither of which has occurred. The furthest-out claim on the scorecard.

Full analysis: Will there be superintelligence? →

Source: situational-awareness.ai · Verdicts based on public retrospectives & benchmarks

The 2027 clock is ticking.

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His 2027 vs everyone else

Public AGI timelines · Mid-2026
Forecaster AGI timeline Camp
Elon Musk (xAI) By end of 2026 Most aggressive
Leopold Aschenbrenner 2027 "strikingly plausible" This scorecard
Demis Hassabis (DeepMind) ~50% by 2030 Lab leader, cautious
Samotsvety (pro forecasters) ~28% by 2030 Best track record
Metaculus community (~2,000 forecasters) 25% by 2029 · 50% by 2033 Crowd consensus
Andrej Karpathy (ex-OpenAI) ~A decade out Architecture skeptic
AI researcher survey (2,778 respondents) 50% by 2040 Academic median

Definitions of "AGI" vary by forecaster — direct comparison is approximate. Notably, expert medians have compressed from ~2060 to ~2033 in six years.

Changelog — proof this scorecard is alive

Every update to verdicts, evidence, or framing gets logged here.
Jun 12, 2026

Logged Anthropic's reversal of Fable 5's silent restrictions on frontier-LLM development — flagged requests now visibly fall back to Opus 4.8 with notification. Recorded as evidence context under the open-source / moat verdict (capability gating proved hard to sustain even for one release cycle). No grade change.

Jun 11, 2026

Published the full two-year analysis with pre-registered flip conditions. Revenue framing expanded to cite both Harris's evaluation (~$60B most generous) and spring-2026 lab reporting (OpenAI ~$25B+, Anthropic ~$19–20B annualized) following EA Forum discussion.

Jun 10, 2026

Scorecard launched at the essay's two-year mark: 3 on track, 1 wrong, 2 open, 2 pending.

Frequently asked questions

Was Aschenbrenner right about AGI by 2027?

Partially on track as of mid-2026. Compute scaling has roughly held, AI investment has exceeded his projections, and frontier models perform at or above the level he predicted for 2025/26. But full AGI — models autonomously doing AI research — remains unconfirmed, and his call that open-source would fade has been clearly wrong. See the full verdict →

What is Situational Awareness?

A 165-page essay published in June 2024 by former OpenAI researcher Leopold Aschenbrenner, predicting AGI by 2027, an intelligence explosion to superintelligence by decade's end, trillion-dollar compute clusters, and a US-China race over AI. Aschenbrenner went on to found Situational Awareness LP, a hedge fund now managing over $5 billion. Track every prediction →

How far behind are Chinese AI labs?

As of 2026, open-weight models like DeepSeek V4 and Qwen 3.7 Max trail the proprietary frontier by an estimated 3–6 months — much closer than Aschenbrenner's framework assumed, driven by aggressive open-weight releases and dramatically lower pricing. Why this is his clearest miss →

📋 All AGI questions, answered → Was Aschenbrenner right? Will AGI arrive by 2027? Did open source fade? Aschenbrenner vs Metaculus All predictions tracked When will AGI arrive? Who is Aschenbrenner? Situational Awareness summary Aschenbrenner vs Hassabis Will the US govt build AGI? Intelligence explosion 2027? Superintelligence in the 2030s? Is AI compute still scaling? Trillion-dollar AI capex? Can AI replace knowledge workers? Will AI cause mass unemployment? What jobs are safe from AI? Will AI take over? Is AGI inevitable? Aschenbrenner vs Musk Is China beating the US to AGI? Situational Awareness vs AI 2027 Is AGI just hype? Will AI replace programmers? Hassabis's AGI prediction Musk's AGI prediction Is the AI capex a bubble? What is superintelligence? AI orders of magnitude What is unhobbling? How close are we to AGI? DeepSeek vs OpenAI What is AI 2027? US–China AI arms race What is GDPval? Karpathy's AGI prediction 🏆 Who's winning the AGI bet? 📅 AI prediction receipts 📋 Will AI take my job? 60-sec check 💰 AI Investing Hub: who's betting what 🎲 The Future Bet: what do you bet happens? What is SWE-Bench? AI progress in 2026 so far Are scaling laws dead? What is AGI? Is ChatGPT AGI? AI vs human intelligence How fast is AI improving? Narrow vs general AI How will we know AGI arrived? What is the singularity? Altman's AGI prediction Amodei's AGI prediction AGI vs superintelligence The full timeline, graded Altman vs Musk on AGI Altman vs Amodei Musk vs Hassabis Karpathy vs Altman Data for AI agents

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