SimpleFunctions
Winner-take-all answer·3 source contracts·Kalshi 3·refreshed just now·Closes Dec 31, 2026 · 161d

Which AI company will have the best coding model on Dec 31, 2026

Leader sits at 60% across 3 bound outcomes, runner-up at 28%. This is a winner-take-all market — the headline is the leader’s price, not an arithmetic mean.

Leader probability

60%

Anthropic

runner-up 28¢leader 60¢

Outcomes

3

winner-take-all

Runner-up

28¢

OpenAI

Spread

32pp

contested

24h volume

$294

thin orderbook

Closes

Dec 31, 2026

161 days

Venue

Kalshi

3 bound

30-day trend

0%50%100%-30d-3w-2w-1wtodayAnthropic: 59% (29 days, 29 points)Anthropic: 59% on 2026-07-22OpenAI: 29% (29 days, 27 points)OpenAI: 29% on 2026-07-22xAI: 7% (29 days, 20 points)xAI: 7% on 2026-07-21
Anthropic59¢OpenAI29¢xAI7¢
Top 3 candidates by current price · 29d

Bracket family

How the bracket ladder is priced.

Each row is one outcome on the venue. Sorted by 24h volume — the heaviest book is at the top.

Analysis

This probability reflects traders' assessment that Anthropic will be recognized as having the best coding model by year-end 2026. The 55% lead over OpenAI's 37% suggests meaningful confidence in Anthropic's trajectory, though the relatively narrow margin indicates genuine uncertainty. Market pricing will likely shift based on benchmark performance—coding competitions, GitHub Copilot adoption metrics, and public model releases throughout the second half of 2026. The lack of a single formal "winner" definition means traders are inferring consensus from developer adoption, enterprise deployment, and performance on standardized coding tests. Resolution will depend on which models demonstrate superior performance on tasks like algorithm generation, bug detection, and code completion accuracy. The 6-7 month timeframe allows for significant model updates from all competitors.

  • Model release timing: Whether Anthropic, OpenAI, or Google releases a new coding-specialized model in H2 2026 that outperforms existing benchmarks
  • Benchmark results: Performance scores on standardized coding evaluation suites (e.g., HumanEval, LeetCode-style problems) published before year-end
  • Enterprise adoption metrics: Real-world usage data showing which models are selected by major developers and integrated into commercial tools
  • Developer preference indicators: GitHub discussions, Stack Overflow signals, and industry surveys reflecting which models are considered superior by practitioners
  • Definition and judging criteria: Ambiguity around what constitutes 'best'—whether measured by accuracy, speed, adoption, or independent expert assessment

What moved the line

  • Jul 16Anthropic5pp5954¢ · Kalshi
  • Jul 19Anthropic5pp5661¢ · 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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