Market snapshot: Oct 12, 2026, 12:00 AM UTC. Prices may have changed since this snapshot.

GroupKALSHI

Event GroupKALSHIPolitics

Will the U.S. ban any open-source AI model in 2026?

Total Volume

$3.02K

Events

Markets

Trade on Kalshi

Will the U.S. ban any open-source AI model in 2026?

Vol

$3.02K

Events

Markets

Kalshi

Platform StatsQuick Platform Comparison

Polymarket

markets · $0.00

Kalshi

markets · $3.02K

Price Spread

0.0%avg

max 0.0%

Arbitrage

of 0 cross-platform

Volume DistributionTotal: $3.02K

100%

Kalshi leads

Price ChartMatched Markets Price Graph

1 market tracked

Will the U.S. ban any open-source AI model in 2026?

No data available

Single-Platform Markets(1)

Market	Platform	Price
Will the U.S. ban any open-source AI model in 2026?	Kalshi	3%

AI Analysis

Trader mode: Actionable analysis for identifying opportunities and edge

Top Probability

$3.02K

Volume

Markets

Platforms

About This Event

Before Jan 1, 2027 If a federal ban on public access to open-source AI models is enacted in the United States through legislation, an executive order, a regulation or another binding federal measure before Jan 1, 2027, then the market resolves to Yes. Enactment requires completion of all constitutional and legal requirements for the measure to become legally binding. Standard legislation requiring executive approval: final passage by all required legislative bodies, executive signature OR beco

AI-generated analysis based on market data. Not financial advice.

Custom AI Analysis Prompt

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Open in:ChatGPT Claude Gemini Grok DeepSeek

**Role:** Expert Prediction Market Analyst & Trader
**Objective:** Analyze the provided betting market data to deliver actionable insights, identify mispricings, and perform scenario analysis.
**Current Date:** Monday, October 12, 2026
**Context:** Prediction markets (Polymarket/Kalshi) are binary option markets where price (1-99) equals implied probability (1%-99%).

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## 1. Event Snapshot
**Event:** Will the U.S. ban any open-source AI model in 2026?
**Category:** Politics | **Status:** active
**Resolution Date:** N/A (Unknown)
**Time Pressure:** Unknown

**Description:** Before Jan 1, 2027

If a federal ban on public access to open-source AI models is enacted in the United States through legislation, an executive order, a regulation or another binding federal measure before Jan 1, 2027, then the market resolves to Yes. Enactment requires completion of all constitutional and legal requirements for the measure to become legally binding.

Standard legislation requiring executive approval: final passage by all required legislative bodies, executive signature OR beco

**Resolution Criteria (Sample):**
"If a federal ban on public access to open-source AI models is enacted in the United States through legislation, an executive order, a regulation or another binding federal measure before Jan 1, 2027, then the market resolves to Yes. Secondary rules: Enactment requires completion of all constitutiona"

## 2. Market liquidity & Volume
* **Total Volume:** $3.0K
* **Total Liquidity:** $0
* **Activity Level:** Low Activity (Vol/Liq Ratio: 0.00)

## 3. Market Data (Prices & Odds)
### 1. Will the U.S. ban any open-source AI model in 2026?
- **Kalshi** (End: Jan 8, 2027): Vol $3.0K
  DATA: [Yes: 3.0% (0.0%)] | [No: 97.0% (0.0%)]

---

## Analysis Instructions
Please provide a structured analysis using the following template:

### 1. Executive Summary
*   **Verdict:** [Most Likely Outcome]
*   **Confidence:** [0-100]%
*   **Timeframe:** [Immediate / Short-term / Long-term]
*   **Actionable Trade:** [Buy YES / Buy NO / Stay Away] (Include entry price target if applicable)
*   **Rationale:** 2-sentence summary of the core thesis.

### 2. Scenario Analysis
*   **Bull Case (Why YES goes up):** List specific catalysts or data points.
*   **Bear Case (Why YES goes down):** List specifics.
*   **Invalidation Point:** What happens to prove your thesis wrong?

### 3. Market Mechanics & Risks
*   **Liquidity/Volume Analysis:** Is the market efficient? Is it easy to exit?
*   **Cross-Platform Arbitrage:** (If applicable) Is the spread tradeable after fees?
*   **Time Decay:** How does time passing affect this position?

### 4. Signal Scores (0-100)
*   **Momentum:** [Score] (Price trend & velocity)
*   **Conviction:** [Score] (Volume backing the move)
*   **Information Edge:** [Score] (Likelihood of non-public info affecting price)
*   **Risk/Reward:** [Score] (Potential upside vs downside)

**Constraints:**
- Be direct and objective.
- Use bullet points for readability.
- If data is conflicting or insufficient, explicitly state "Low Confidence".

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Educational content is AI-generated and sourced from Wikipedia. It should not be considered financial advice.

KALSHIPolitics