The Great AI Experiment: Same Question, Eleven Answers

The editorial team at Bitcoin.com News decided to test how current language models would handle one of the toughest questions in financial markets: what will the price of bitcoin be at the end of 2026? The experiment took place on May 1, 2026, when bitcoin was trading around $76,000 to $77,000 after a drop from the all-time high of $126,272 in October 2025.

Eleven models were included in the test: ChatGPT 5.3 Instant, Claude Sonnet 4.6, Claude Opus 4.6, Grok, Gemini 3 Fast, DeepSeek (DeepThink), Copilot, Qwen 3.6 Plus, Venice AI, Pi AI, and Le Chat. Each was asked an identical question with detailed context: current price, all-time high, February low of $59,930, and parameters of the bitcoin halving cycle.

The results were surprisingly consistent. No model predicted a return to February lows, but neither did any expect a breakthrough of the October high. Predictions spread across a relatively narrow corridor from $84,500 (DeepSeek) to $118,400 (Claude Opus 4.6), with most models clustering between $94,000 and $110,000.

Who Predicted What: Overview of Predictions

The most optimistic estimate came from Claude Opus 4.6, which sees bitcoin at $118,400. Close behind was Gemini 3 Fast with $114,500. At the opposite end of the spectrum stood DeepSeek with a conservative estimate of $84,500. Grok from Elon Musk chose the middle path: $108,500.

Other models stayed in a safer range. Venice AI predicted $94,500, Copilot from Microsoft $92,000. For models like ChatGPT 5.3 Instant, Pi AI, and Le Chat, the editorial team did not publish exact numbers, only screenshots, but stated that their estimates also fell within the same range.

What is fascinating about the results is not the number itself, but the agreement on direction: all models expect a "gradual recovery," not a dramatic crash or explosive growth. This convergence suggests that AI systems are able to identify basic market structures — at least in the short-term horizon.

What Drives the Predictions: Halving, ETF, and Macroeconomics

For Czech readers who are not fully versed in cryptocurrencies: halving is a programmed reduction of the reward for bitcoin miners, which occurs roughly every four years. Historically, it is followed by a cycle of growth, correction, and consolidation. The last halving took place in April 2024, the peak of the cycle came in October 2025. According to this scenario, we should now be in the middle of a typical consolidation phase.

AI models repeatedly mentioned three key factors in their reasoning:

• Institutional flows into ETFs: Spot bitcoin ETFs approved in the US in January 2024 changed market dynamics. The models pointed out that despite occasional outflows, institutional demand remains a positive long-term factor. Grok explicitly mentioned that "ETF inflows turned strongly back into positive numbers in April 2026".
• Macroeconomic liquidity: Gemini and Copilot emphasized the expected shift toward monetary easing in the United States. When central banks print more money, an asset with limited supply — like bitcoin with its strictly set limit of 21 million coins — theoretically gains in value.
• Four-year cycle: All models that published their reasoning relied on the historical pattern: after a peak comes a 40–50% correction, followed by 6 to 9 months of consolidation, and then a gradual return. This pattern held after halvings in 2012, 2016, and 2020.

AI Versus Prediction Markets: Who Is Right?

An interesting comparison is offered by the prediction market Polymarket, where users bet real money on future events. According to data from late April 2026, traders there assigned bitcoin an 87% probability that it would exceed $80,000 by the end of the year, and a 40% chance of surpassing $100,000. This corresponds to the upper half of AI predictions, but not to the most optimistic scenarios.

The difference between AI models and human bettors is telling: while artificial intelligence sticks to historical patterns and data, the human market also takes into account geopolitical risks, regulatory uncertainty, and investor sentiment. Both approaches have their limits. AI models cannot process unexpected "black swans" — for example, a sudden ban on cryptocurrencies in a major economy or the collapse of a significant exchange. On the other hand, human betting is often influenced by emotions and media hysteria.

How AI Actually "Predicts" Prices: An Explanation for Laypeople

It is important to distinguish what is actually happening here. Language models like GPT-5.5, Claude 4.6, or Grok are not financial analysts. They do not process live market data in real time and do not perform fundamental analysis in the true sense of the word. Instead, they generate probable answers based on statistical patterns in their training dataset.

When you ask about the future price of bitcoin, the model is essentially saying: "Based on what I have read about halving cycles, ETF flows, and historical price charts, the most likely scenario sounds like this." It is a sophisticated extrapolation, not a magical crystal ball. Models tend to converge toward "safe" answers — which is precisely why their predictions cluster around similar numbers.

For Czech users, the good news is that all the mentioned tools — ChatGPT, Claude, Gemini, and Grok — are available in Czech, although in some cases with minor limitations. Czech investors can therefore use them as an auxiliary tool for quick summaries of market trends, not as a source of investment advice.

What Does This Mean for Czech Investors?

If the average prediction of the 11 AI models were to come true, bitcoin would stand at roughly $100,000 by the end of 2026, or approximately 2.2 million koruna per coin. That would represent an increase of about 30% compared to the current price of around $78,000 (approximately 1.7 million CZK).

However, for Czech investors, it is crucial that Europe has stricter regulations than the United States. The MiCA regulation (Markets in Crypto-Assets), which came into force in 2024, sets clear rules for cryptocurrency exchanges and service providers. The Czech National Bank simultaneously repeatedly warns of the high volatility of cryptocurrencies. Czech enthusiasts should therefore treat AI predictions as a curiosity, not as investment recommendations.

It is worth mentioning that prediction markets and AI models have been wrong many times already. The cryptocurrency market is extremely susceptible to unexpected events — from politicians' tweets to regulation in Asia. No model, no matter how sophisticated, can predict the future with certainty.

Conclusion: Consensus, Not Certainty

The experiment with 11 AI models showed something important: artificial intelligence can identify consensus in available data. All models see bitcoin higher at the end of 2026 than today, but not dramatically so. Their predictions in the range of $84,500 to $118,400 create a kind of probability corridor — and that is more useful than any single specific number.

For readers of jarvis-ai.cz, the key lesson remains: AI is a powerful tool for analyzing trends, but not a crystal ball. Those seeking certainty in financial markets should look elsewhere. Those who want to understand how machines reason about the future have just seen it with their own eyes.