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

GroupPOLYMARKET

Event GroupPOLYMARKETTech

Meta's "Watermelon" model released by...?

Name: Meta's "Watermelon" model released by...?
End: 2026-11-30T23:59:00.000Z

Total Volume

$92.72K

Events

Markets

Trade on Polymarket

Meta's "Watermelon" model released by...?

Vol

$92.72K

Events

Markets

Polymarket

Platform StatsQuick Platform Comparison

Polymarket

markets · $92.72K

Kalshi

markets · $0.00

Price Spread

0.0%avg

max 0.0%

Arbitrage

of 0 cross-platform

Volume DistributionTotal: $92.72K

100%

Polymarket leads

Price ChartMatched Markets Price Graph

3 markets tracked

Meta's Watermelon released by November 30, 2026?

No data available

Single-Platform Markets(3)

Market	Platform	Price
Meta's Watermelon released by November 30, 2026?	Poly	95%
Meta's Watermelon released by October 31, 2026?	Poly	72%
Meta's Watermelon released by October 15, 2026?	Poly	47%

AI Analysis

Trader mode: Actionable analysis for identifying opportunities and edge

95%

Top Probability

$92.72K

Volume

Markets

Platforms

About This Event

On September 2, 2026, alongside the launch of Muse Spark 1.3, Meta announced a roadmap "including bigger models" (https://research.meta.ai/blog/introducing-muse-spark-1-3). Credible reporting has identified Meta's next-generation frontier model by the internal codename "Watermelon." This market will resolve to "Yes" if Meta releases "Watermelon" or a model confirmed to be the model referenced above, and that model is made available to the general public by the listed date (ET). Otherwise, this

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%).

---

## 1. Event Snapshot
**Event:** Meta's "Watermelon" model released by...?
**Category:** Tech | **Status:** active
**Resolution Date:** Nov 30, 2026 (50 days left)
**Time Pressure:** Low

**Description:** On September 2, 2026, alongside the launch of Muse Spark 1.3, Meta announced a roadmap "including bigger models" (https://research.meta.ai/blog/introducing-muse-spark-1-3). Credible reporting has identified Meta's next-generation frontier model by the internal codename "Watermelon."

This market will resolve to "Yes" if Meta releases "Watermelon" or a model confirmed to be the model referenced above, and that model is made available to the general public by the listed date (ET). Otherwise, this 

## 2. Market liquidity & Volume
* **Total Volume:** $63.3K
* **Total Liquidity:** $3.7K
* **Activity Level:** High Turnover (Vol/Liq Ratio: 16.98)

## 3. Market Data (Prices & Odds)
### 1. Meta's Watermelon released by October 31, 2026?
- **Polymarket** (End: Oct 31, 2026): Vol $43.8K
  DATA: [Yes: 71.5% (0.0%)] | [No: 28.5% (0.0%)]

### 2. Meta's Watermelon released by November 30, 2026?
- **Polymarket** (End: Nov 30, 2026): Vol $12.4K
  DATA: [Yes: 94.5% (0.0%)] | [No: 5.5% (0.0%)]

### 3. Meta's Watermelon released by October 15, 2026?
- **Polymarket** (End: Oct 16, 2026): Vol $7.1K
  DATA: [Yes: 47.0% (0.0%)] | [No: 53.0% (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.

POLYMARKETTech