SimpleFunctions
6 source contracts·Kalshi 6·refreshed just now·Closes Jan 1, 2027 · 102d

Will Mistral have a top-ranked AI model before 2027

Liquidity-weighted aggregate sits at 8% across 6 Kalshi contracts.

Implied probability

8%
0%50%100%

Kalshi

8%

6 contracts

Polymarket

not bound

Cross-venue gap

single venue

24h move

no pin

24h volume

$1K

6 contracts

Closes

Jan 1, 2027

102 days

30-day trend

0%50%100%-30d-3w-2w-1wtodayAggregate: 10% (25 days, 25 points)Aggregate: 10% on 2026-09-19
Aggregate of 6 contracts · 25d

Bracket families

6 clusters across 6 contracts.

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

Cluster 1

Will OpenAI have a top-ranked AI model before 2027

1 contract$1K

Cluster 2

Will Meta have a top-ranked AI model before 2027

1 contract$101

Cluster 3

Will Alibaba have a top-ranked AI model before 2027

1 contract$85

Cluster 4

Will xAI have a top-ranked AI model before 2027

1 contract$43

Cluster 5

Will Nvidia have a top-ranked AI model before 2027

1 contract$0

Cluster 6

Will Deepseek have a top-ranked AI model before 2027

1 contract$0

Analysis

This probability estimates the likelihood that Mistral will develop a model ranked among the top performers globally by end-2026. At 11%, the market suggests Mistral faces significant hurdles compared to better-capitalized competitors like OpenAI (35%) and xAI (17%). The current assessment reflects Mistral's resource constraints relative to incumbents and the rapid consolidation of AI capabilities among larger labs. Key factors driving this level include Mistral's access to funding and compute, the benchmark methodology used to rank models (which may favor certain architectures or training approaches), and whether any new model release reaches sufficient capability thresholds before year-end. The main catalyst for this market will be major benchmark releases in late 2026, particularly comprehensive evaluations like MMLU, ARC, or proprietary leaderboards where model rankings become publicly visible. Performance of Mistral's recent releases and any announced major model drops between now and December 2026 will directly inform belief updates.

  • Mistral's compute allocation and funding trajectory relative to OpenAI, Anthropic, and xAI through late 2026
  • Definition and methodology of 'top-ranked' — which specific benchmarks (MMLU, ARC, Chatbot Arena, others) determine winners
  • Timeline of Mistral's announced model releases: whether any major new model ships before end-2026
  • Current capability gaps: how Mistral's latest models (as of August 2026) compare numerically on standard benchmarks to leading alternatives
  • Aggregate market probability for competitors: OpenAI at 35% and xAI at 17% suggest concentrated belief in fewer winners

What moved the line

  • Sep 18OpenAI7pp3023¢ · Kalshi
  • Sep 17OpenAI4pp3430¢ · Kalshi
  • Sep 17xAI4pp128¢ · 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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