# Will any AI model have a score of at least 1750 before Jan 1, 2027

> At least 1520 score leads at 78%, runner-up 66% across 6 winner-take-all outcomes — refreshed 4 min ago.

URL: https://simplefunctions.dev/odds/aispike
Updated: 2026-06-29T01:20:50.637Z
Category: technology
Status: active
Closes: 2027-01-01

## Headline

- Leader: At least 1520 score at 78%
- Runner-up: At least 1530 score at 66%
- Outcomes: 6 (winner-take-all)
- Venue: Kalshi (6 contracts)
- 24h volume: $5

## Bound contracts (6)

| Outcome | Price | 24h | Volume | Venue | Slug |
|---|---|---|---|---|---|
| At least 1520 score | 78¢ | +1pp | $0 | kalshi | /markets/will-any-ai-model-have-a-score-of-at-least-1520-be-kalshi-kxaispike-27b-1520 |
| At least 1530 score | 66¢ | +1pp | $0 | kalshi | /markets/will-any-ai-model-have-a-score-of-at-least-1530-be-kalshi-kxaispike-27b-1530 |
| At least 1540 score | 45¢ | +1pp | $0 | kalshi | /markets/will-any-ai-model-have-a-score-of-at-least-1540-be-kalshi-kxaispike-27b-1540 |
| At least 1550 score | 35¢ | +3pp | $5 | kalshi | /markets/will-any-ai-model-have-a-score-of-at-least-1550-be-kalshi-kxaispike-27-1550 |
| At least 1600 score | 12¢ | −1pp | $0 | kalshi | /markets/will-any-ai-model-have-a-score-of-at-least-1600-be-kalshi-kxaispike-27-1600 |
| At least 1650 score | 7¢ | — | $0 | kalshi | /markets/will-any-ai-model-have-a-score-of-at-least-1650-be-kalshi-kxaispike-27-1650 |

## 30-day trajectory

| Day | At least 1520 score | At least 1530 score | At least 1540 score |
|---|---|---|---|
| 2026-06-26 | 76 | 65 | 43 |
| 2026-06-27 | 77 | — | 44 |
| 2026-06-28 | 78 | 66 | 45 |

_3 days of price history captured. Each row is the daily mean of intraday 5-min captures._

## What moved the line

- 2026-06-27 · At least 1550 score +3pp 32→35¢ · kalshi

## Analysis

This asks whether any AI model will achieve a score of at least 1750 by year-end 2026, currently priced at 76% probability. The market structure shows declining prices at higher thresholds: 1520 is 76%, 1550 drops to 34%, and 1600 falls to 13%, suggesting uncertainty concentrates around whether models will exceed mid-range performance levels. The main drivers are: the rate of AI capability scaling in recent months, current best-model performance relative to the 1750 target, and the remaining ~6 months for frontier labs to release improved versions. Resolution hinges on which benchmarks define "score" and official reporting by major AI labs before December 31, 2026. Major model releases or benchmark updates in Q3-Q4 2026 would most directly impact this outcome.

### Key factors

- Current performance of leading AI models relative to 1750 threshold and historical acceleration rates over past 12 months
- Definition and standardization of the scoring mechanism—whether it references a specific published benchmark (e.g., ARC, MMLU, specialized domain scores)
- Number and timing of major AI model releases between now and Dec 31, 2026, and their reported performance levels
- Whether the 1750 target represents an incremental improvement from current leaders or a significant capability jump
- Clarity on reporting standards—which labs' official claims will count as valid evidence for resolution

## Methodology

Headline is the **leader's price**, not an arithmetic mean — averaging disjoint winner-take-all outcomes is meaningless. Per-outcome prices come from the venue's last-traded mid; cross-venue values are simple means across contracts on each venue.

## How to use this data

- HTML: https://simplefunctions.dev/odds/aispike
- JSON: https://simplefunctions.dev/api/public/odds?slug=aispike

## License

CC-BY-4.0. Attribute "SimpleFunctions" with a link to https://simplefunctions.dev. See https://simplefunctions.dev/legal for terms.