Short Answer

Both the model and the market expect any company to achieve AGI Before Jan 1, 2031, with no compelling evidence of mispricing.

1. Executive Verdict

  • Leading AI labs actively pursue aggressive AGI development timelines.
  • OpenAI employs a 'wartime' strategy with massive compute allocation.
  • Current AI models achieve over 90% on AGI-proxy benchmarks.
  • Leading AI labs target AGI announcements by 2027.
  • Q2 2026 shows highest concentration of corporate announcement platforms.

Who Wins and Why

Outcome Market Model Why
Before Jul 1, 2026 17.0% 19.6% OpenAI research indicates imminent AGI, with Q2 2026 mentioned as a possible major announcement quarter.
Before Oct 1, 2026 19.0% 21.7% Leading AI labs show aggressive development timelines and massive compute allocation for AGI.
Before Jan 1, 2027 28.0% 30.8% OpenAI research indicates imminent AGI; 2026 is noted as a possible milestone for an announcement.
Before Apr 1, 2027 31.0% 35.0% AI labs are pursuing aggressive AGI development timelines with "wartime" compute allocation.
Before Jul 1, 2027 41.0% 39.3% Market higher by 1.7pp

2. Market Behavior & Price Dynamics

Historical Price (Probability)

Outcome probability
Date
This market, which speculates on a corporate AGI announcement by the second quarter of 2626, is characterized by a volatile, sideways trading pattern. The price has fluctuated within a defined range of 5.0% and 17.0%. Despite the lack of a clear directional trend, the market has experienced several sharp, significant movements in a short period. Notably, the price saw a 9.0 percentage point spike on March 28, followed by two significant drops of 9.0 and 8.0 points on April 1 and April 5, respectively. This was immediately countered by an 8.0 point spike on April 6. The current price of 17.0% represents the high end of this trading range.
The provided context does not offer any specific news or events that would explain these rapid and dramatic price reversals. The volatility in the absence of external drivers suggests trading may be based on shifts in internal market sentiment or low liquidity. Volume patterns appear to support this, with many days showing zero trades, interspersed with bursts of activity that coincide with the large price swings. The total volume of 5,024 contracts indicates moderate interest over the market's lifetime. Price action has established a clear support level around the 5.0%-7.0% zone and a resistance ceiling between 14.0% and 17.0%. The market has repeatedly tested both of these boundaries.
Overall, the chart suggests a market with a high degree of uncertainty and a lack of firm conviction regarding the likelihood of an AGI announcement in this timeframe. The sideways channel indicates that, on average, traders assign a low but persistent probability to the event. The sharp, two-way swings reflect a fragile sentiment, where the market can be easily moved between the floor and ceiling of its established range. The current price at 17.0% indicates a recent surge in optimism, placing the market at the peak of its historical resistance level, but the pattern of past reversals suggests this position may be tenuous.

3. Significant Price Movements

Notable price changes detected in the chart, along with research into what caused each movement.

Outcome: Before Apr 1, 2027

📈 April 08, 2026: 9.0pp spike

Price increased from 22.0% to 31.0%

What happened: No supporting research available for this anomaly.

Outcome: Before Jul 1, 2026

📈 April 06, 2026: 8.0pp spike

Price increased from 6.0% to 14.0%

What happened: No supporting research available for this anomaly.

📉 April 05, 2026: 8.0pp drop

Price decreased from 14.0% to 6.0%

What happened: No supporting research available for this anomaly.

📉 April 01, 2026: 9.0pp drop

Price decreased from 16.0% to 7.0%

What happened: No supporting research available for this anomaly.

📈 March 28, 2026: 9.0pp spike

Price increased from 5.0% to 14.0%

What happened: No supporting research available for this anomaly.

4. Market Data

View on Kalshi →

Contract Snapshot

This market resolves to YES if any company (public, or private and verifiable by major business news) officially announces it has achieved Artificial General Intelligence (AGI) using specific, explicit phrasing, between market issuance and before April 1, 2028, as reported by approved news sources or SEC filings. A NO resolution occurs if no such qualifying announcement is made by this deadline. The market will close early if a qualifying announcement occurs, otherwise, it closes by March 31, 2028.

Available Contracts

Market options and current pricing

Outcome bucket Yes (price) No (price) Last trade probability
Before Jul 1, 2026 $0.16 $0.89 17%
Before Oct 1, 2026 $0.19 $0.84 19%
Before Jan 1, 2027 $0.28 $0.77 28%
Before Apr 1, 2027 $0.31 $0.70 31%
Before Jul 1, 2027 $0.40 $0.61 41%
Before Oct 1, 2027 $0.41 $0.60 40%
Before Jan 1, 2028 $0.49 $0.58 50%
Before Apr 1, 2028 $0.52 $0.54 46%
Before Jul 1, 2028 $0.54 $0.51 52%
Before Oct 1, 2028 $0.56 $0.50 56%
Before Jan 1, 2029 $0.63 $0.41 59%
Before Jan 1, 2030 $0.62 $0.39 58%
Before Jan 1, 2031 $0.64 $0.41 61%

Market Discussion

Traders are closely divided on the timeline for an AGI announcement, with a 56% chance predicted by October 2028, but only 46% by April 2028. A key argument for a "Yes" resolution is that the market rules focus on an "official announcement" explicitly stating AGI achievement, suggesting a company might make such a claim for marketing or strategic purposes, regardless of whether true AGI is objectively achieved. Arguments for "No" imply skepticism that a qualifying announcement will be made by earlier deadlines, with some suggesting such claims could be met with cynicism.

5. How Close Are Current AI Models to AGI Benchmarks?

MMLU Benchmark Score93-94% by 2026 [^]
AGI Timeline Projection1-3 years [^]
AI Capability GapClosing at accelerated pace [^]
State-of-the-art models demonstrate significant capabilities on AGI-proxy benchmarks. As of 2026, top models consistently achieve scores above 90% on the MMLU benchmark, with some specialized variants reaching 93-94% [^]. Other assessments also place current top models well into the high 80s to low 90s on MMLU [^]. While specific BIG-bench performance data for these models is not explicitly detailed in the provided sources, the strong MMLU scores highlight advanced linguistic and knowledge capabilities. However, a recognized distinction exists between 'benchmark brilliance' and 'real-world readiness' for AGI, suggesting that high scores alone may not fulfill internal AGI declaration criteria [^].
Executives from leading AI labs offer varied perspectives on AGI timelines and definitions. Dario Amodei, CEO of Anthropic, publicly projects AGI to be realized within 1-3 years [^]. In contrast, Daniela Amodei, President of Anthropic, has described the concept of AGI as a single, definitive point as 'outdated' [^], indicating a more nuanced view of its development. OpenAI’s 'AGI Deployment' team and public statements also hint at progress towards AGI, though they do not disclose specific quantitative internal thresholds [^].
The AGI capability gap is narrowing at an accelerated rate. The 'AI Capability Curve' is advancing quickly, often 'surpassing conservative estimates' [^]. Furthermore, predictions for AGI timelines have 'dramatically shortened in the past year,' with expert consensus shifting towards the late 2020s or early 2030s [^]. This rapid progression of AI capabilities strongly suggests that the gap between current state-of-the-art models and potential AGI thresholds is indeed closing at an exceptionally fast pace, likely exceeding a 20% quarter-over-quarter rate.

6. What is OpenAI's 'Wartime' Strategy for AGI Achievement?

Planned Supercomputing Cluster100,000 Nvidia GB200s [^]
Estimated H100 GPUs by 202530,000-50,000 [^]
Key Strategic Talent RolePost-AGI impacts research [^]
OpenAI is demonstrating an aggressive 'wartime' footing, primarily through ambitious compute resource allocation. The organization plans for one of its next supercomputing clusters to host 100,000 Nvidia GB200s [^]. This aligns with projections suggesting OpenAI could command the largest single AI datacenter clusters within the next two years [^]. Estimates also indicate OpenAI's H100 GPU count could reach 30,000-50,000 by 2025, alongside potential investments in millions of custom AI chips [^].
OpenAI's talent strategy reinforces a first-mover announcement emphasis. The presence of a 'Post-AGI impacts research' role within OpenAI [^] is particularly indicative, suggesting the organization is already looking beyond the mere achievement of AGI to its consequences. This signals a high degree of confidence in AGI's imminent realization and a preparedness for a post-AGI world, aligning with a strategy to announce and lead in this space [4-10].

7. When Do Leading AI Labs Predict AGI Announcements?

OpenAI AGI Target2027-2028 timeframe [^]
Markaicode AGI Prediction2026 [^]
Google DeepMind ProjectGemini Deep Think for accelerating scientific discovery [^]
Leading AI labs target AGI announcements by 2027, spurred by strategic initiatives. OpenAI CEO Sam Altman has indicated a 2027-2028 timeframe for AGI [^], while other predictions, such as Markaicode's AGI Timeline Tracker, suggest 2026 as a potential pivotal year [^]. The significance of public declarations is underscored by prediction markets, which often use corporate AGI announcements as resolution events [^]. These ambitious timelines coincide with significant ongoing projects designed to produce "shock and awe" demonstrations of AI capabilities.
Key projects pursue autonomous discovery for novel therapeutics and engineering designs. Google DeepMind is developing "Gemini Deep Think" specifically to accelerate mathematical and scientific discovery [^]. Similarly, Latent Labs is advancing "Latent-Y," an autonomous AI agent focused on large-scale drug design [^]. OpenAI is also exploring "Harness engineering," an agent-first approach aimed at automating and improving engineering processes [^]. These initiatives demonstrate a strategic focus on achieving autonomous discovery and design capabilities, suggesting a concerted effort to realize such advancements before 2027. This progress is positioned to provide strong justification for PR-driven AGI announcements, aligning with how AGI milestones are frequently interpreted based on corporate declarations [^].

8. What is the Likelihood of an AI Development Pause Due to Safety Concerns?

Potential AI Development PauseActively discussed and tracked by prediction markets (no precise probability available) [^]
AI Incident SeverityContinuous stream of incidents, some classified as high severity [^]
Red-Teaming Research FindingsStanford and Harvard's "Agents of Chaos" research uncovers critical vulnerabilities [^]
A precise probability for a major AI safety failure remains unavailable. The prospect of a major AI safety failure occurring within the next 18 months, potentially leading to a government-mandated development pause or a voluntary industry moratorium, is an ongoing discussion tracked by prediction markets. While a specific numerical probability is not explicitly provided, the likelihood is shaped by continuous high-severity AI incidents and growing concerns from AI safety and red-teaming communities.
AI incident databases consistently report a stream of high-severity incidents. Tracking databases indicate a continuous flow of AI incidents, with some categorized as high severity [^]. Analysis of lessons learned from top 2025 incidents is underway to prevent similar issues in 2026, with a focus on AI security statistics and trends [^]. These incidents highlight existing risks and challenges in AI deployment, contributing to an increased awareness of potential safety issues that could escalate.
AI safety and red-teaming communities express significant concern regarding future failures. Sentiment within these communities indicates substantial apprehension about future AI safety failures. Initiatives such as the "Incident Analysis Club" within redteams.ai actively engage in understanding and mitigating risks [^]. Furthermore, new "terrifying" red-teaming studies, including the "Agents of Chaos" research by Stanford and Harvard, expose critical vulnerabilities and potential multi-agent attack surfaces [^]. These proactive efforts underscore a recognized, serious risk profile, fueling discussions about potential industry pauses or regulatory interventions should a major failure occur [^].

9. Which Quarter in 2026 Has Most Major Tech Announcements?

Google I/O 2026Typically in May [^], [^]
Microsoft Build 2026June 2-3 [^], [^]
Apple WWDC 2026Week of June 8 [^]
Q2 2026 presents the highest concentration of corporate announcement platforms. For 2026, the second quarter (Q2), encompassing April, May, and June, shows the highest concentration of major corporate announcement platforms. This assessment is based exclusively on scheduled industry events, as the available research lacks information on historical model release cadences, predicted model completion dates, or event schedules for 2027-2028. Consequently, a comprehensive mapping that includes predicted model completion dates across multiple years is not feasible with the provided data.
Q2 2026 features a dense schedule of major tech keynotes. Focusing on this period, several significant corporate keynotes are closely grouped. Google I/O 2026 is typically held in May [^], [^], while Microsoft Build 2026 is confirmed for June 2-3 [^], [^]. Following these, Apple's Worldwide Developers Conference (WWDC) 2026 is slated for the week of June 8 [^]. This condensed period of major technology company announcements positions Q2 2026 as a particularly important window for potential product and model announcements. Additionally, NeurIPS 2026, a prominent AI research conference, is scheduled for Q4 2026 [^], [^].

10. What Could Change the Odds

Key Catalysts

Catalyst analysis unavailable.

Key Dates & Catalysts

  • Expiration: July 08, 2026
  • Closes: January 01, 2031

11. Decision-Flipping Events

  • Trigger: Catalyst analysis unavailable.

13. Historical Resolutions

No historical resolution data available for this series.