SimpleFunctions
7 source contracts·Kalshi 7·refreshed just now·Closes Jan 1, 2027 · 189d

Which company has the second 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

$3K

7 contracts

Closes

Jan 1, 2027

189 days

30-day trend

0%50%100%-30d-3w-2w-1wtodayAggregate: 33% (30 days, 30 points)Aggregate: 33% on 2026-06-25
Aggregate of 7 contracts · 30d

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 probability reflects market expectations that a company other than the leader will hold the second-best AI model by end of April 2026. The 25% aggregate probability suggests traders view this outcome as unlikely but plausible. Two main factors drive the current level: the concentration of recent AI breakthroughs among a few dominant players, which makes it difficult for a second-place competitor to emerge, and uncertainty about which capability dimension matters most for ranking models—coding performance, reasoning, multimodal abilities, or general instruction-following. The outcome depends heavily on how model benchmarks are evaluated in late April, particularly whether official leaderboards and third-party evaluations show a clear separation between first and second place, or whether technical performance remains contested across different domains.

  • Benchmark methodology: Whether end-of-April evaluations prioritize coding benchmarks (favoring Anthropic per Kalshi data) versus general reasoning tasks affects which company places second
  • Polymarket-Kalshi divergence of 7 percentage points suggests material disagreement on likelihood; Polymarket traders price it higher, possibly reflecting greater uncertainty about what 'best model' means
  • Recent contract data shows heavy Anthropic positioning across multiple timeframes (June style control at 67¢, December coding at 59¢), indicating concentrated market belief in their competitive position
  • The 20% Kalshi average versus 27% Polymarket average may reflect different trader bases with different definitions of model quality or different confidence in April timeline data
  • Top trading volume concentrates on 'which company has best' contracts, not second-best, suggesting secondary rankings receive less liquidity and sharper opinion divergence

What moved the line

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