SimpleFunctions
7 source contracts·Kalshi 7·refreshed just now·Closes Jan 1, 2027 · 187d

Which company has the third best AI model end of April

Liquidity-weighted aggregate sits at 18% across 7 Kalshi contracts.

Implied probability

18%
0%50%100%

Kalshi

18%

7 contracts

Polymarket

not bound

Cross-venue gap

single venue

24h move

no pin

24h volume

$667

7 contracts

Closes

Jan 1, 2027

187 days

30-day trend

0%50%100%-30d-3w-2w-1wtodayAggregate: 21% (31 days, 31 points)Aggregate: 21% on 2026-06-27
Aggregate of 7 contracts · 31d

Bracket families

2 clusters across 7 contracts.

These contracts were grouped by title similarity. The headline aggregate combines all clusters; verify the cluster you actually need before quoting a number.

Heads-up — heterogeneous clusters

The top two clusters share only 22% of their title tokens — “Which AI company will have the best coding model on Dec 31, 2026” vs “Which company will release a Fully AI-generated multi-episode scripted series to the public”. The headline aggregate weights both, so the number on this page is meaningful only if the clusters resolve to the same question.

Analysis

This 25% probability represents the estimated chance that a specific company ranks third in AI model capability as of end of April 2026. The slight divergence between trading venues (22% on Kalshi vs. 27% on Polymarket) suggests uncertainty about which companies will occupy the top positions and how to define third place. The probability reflects that leadership in AI capabilities remains contested and frequently reshuffled. Key drivers include continued model releases from major players, benchmark performance data, and how evaluators measure "best" across different use cases. The interpretation depends heavily on whether third place refers to general-purpose models, specialized domains like coding, or overall market perception.

  • No clear consensus exists on ranking methodology—definitions vary between coding ability, general reasoning, multimodal performance, or broader commercial adoption
  • Recent model releases and benchmark results from Anthropic, Google, and OpenAI significantly influence rankings, with coding-specific metrics showing different hierarchies than general benchmarks
  • The substantial volume and price movement in June-dated contracts (Anthropic at 64¢ vs. Google at 26¢) indicates market focus on near-term model releases rather than April positions
  • Trading volume concentrates on June endpoints rather than April, suggesting April rankings carry less predictive interest or have lower resolution clarity
  • Cross-venue gap of 5 percentage points indicates legitimate disagreement about third-place likelihood rather than information asymmetry

What moved the line

  • Jun 23OpenAI4pp3935¢ · Kalshi
  • Jun 21OpenAI3pp3336¢ · Kalshi
  • Jun 22OpenAI3pp3639¢ · Kalshi
  • Jun 23Anthropic3pp5659¢ · Kalshi
  • Jun 24Anthropic3pp5956¢ · Kalshi

Recently closed in technology

These markets stopped trading. Last odds and any captured outcome are shown above — full settlement detail lives at the venue.

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Adjacent prediction questions.

How we compute these odds

SimpleFunctions aggregates live prediction-market contracts from Kalshi and Polymarket. Each slug groups contracts that resolve on the same underlying event, identified by venue event_id.

For binary slugs, the headline probability is the liquidity-weighted mid-price across all bound contracts. For multi-outcome slugs (e.g. elections with 3+ candidates), the headline is the leader’s price; we never arithmetically average disjoint outcomes — that would produce a number with no real-world meaning.

Snapshots refresh every 5 minutes during market hours; daily aggregates are computed at 04:00 UTC. The 30-day sparkline is drawn from per-ticker daily means stored in market_indicator_daily; 24h delta and movement events are derived from the same source.

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