SimpleFunctions
7 source contracts·Kalshi 7·refreshed just now·Closes Jan 1, 2027 · 188d

Which company has the second best Coding 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

$4K

7 contracts

Closes

Jan 1, 2027

188 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 probability reflects the likelihood that a specific company will hold the second-place position in coding AI model performance by late April 2026. The current 26% estimate sits between Kalshi's 20% and Polymarket's 30%, suggesting meaningful disagreement about which company ranks second. The main drivers of this probability are the recent release cycles of major AI models—particularly Claude, GPT-4, and Gemini variants—and benchmark performance on coding-specific tasks like competitive programming and bug-fix evaluation. Market participants are pricing in both known model capabilities and expectations for upcoming releases over the next few months. The key uncertainty centers on whether performance rankings will shift based on new model versions or architectural improvements, with December 2026 contracts showing stronger confidence in Anthropic's coding position long-term but near-term second place remaining contested.

  • Recent coding benchmarks (HumanEval, MBPP, LeetCode performance) and their publication dates determine perceived model rankings
  • Release timing of new model versions from competing companies and whether new versions shift second-place rankings
  • Definition and methodology of what constitutes 'best' and 'second-best'—different benchmarks and evaluation criteria produce different rankings
  • Volume and depth of trading activity differs between venues (Kalshi 7 contracts vs Polymarket 10), potentially reflecting different underlying trader conviction levels
  • Historical pattern of model performance shifts: how often does the second-place company change between quarterly model releases

What moved the line

  • Jun 23OpenAI4pp3935¢ · Kalshi
  • Jun 21OpenAI3pp3336¢ · Kalshi
  • Jun 22OpenAI3pp3639¢ · Kalshi
  • Jun 25xAI3pp58¢ · Kalshi
  • Jun 26xAI3pp85¢ · 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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