Claude Takes the Crown — The Truth Behind 6 Major AI Grid Strategies | OKX & Ai Coin Live Test Results

Season 1 of NOF1's "AI Crypto Trading Live Arena" finally wrapped up at 6:00 AM on November 4, 2025, keeping the crypto, tech, and finance worlds on the edge of their seats.

But the outcome of this "public IQ test for AI" turned out to be somewhat unexpected — the combined $60,000 capital across six models finished at just $43,000, a loss of roughly 28%. Among them, , with a comeback to take first place; meanwhile, all four U.S.-based models ended in the red.

Interestingly, the recent live comparison of six AI models conducted jointly by OKX and Ai Coin didn't focus on short-term trading tactics. Instead, it shifted the spotlight to contract grid strategies — and it was precisely this setup that unearthed the real returns performance of six major AI models: Within contract grid strategies, AI achieved "collective survival" — all models posted positive returns. This suggests that AI models may be better suited to neutral, systematic grid strategies rather than short-term chasing of rallies and selling of dips. Among them, Claude took first place outright, while , which had ranked first in the NOF1 competition, ended up dead last this time. GPT-5 and Gemini performed relatively steadily, securing second and third place respectively; and Grok4 arrived at nearly identical returns despite different strategy settings.

Same AI models — why such a dramatic reversal across two different tests? What insights does this logic hold for strategy and trading users?

6 Major AI Grid Strategies Live Test: Claude Takes the Crown, All Models Post Positive Returns

The "AI Crypto Trading Live Arena" premise was simple: each of six AI models was given $10,000 in capital to independently trade BTC, XRP, and other perpetual contracts on a Perp DEX platform over a two-week period (starting around October 18); only market quantitative data was provided, and the AI had to independently decide long/short direction, leverage, and position size, with a confidence score attached to each decision.

To that end, we applied an equally minimalist setup: under uniform conditions ($1,000 USDT invested per AI, 5x leverage), the six AI models were put through a live test between October 24 and November 4, 2025. Using OKX's BTC/USDT perpetual 1-hour chart, each AI was given grid parameters including price range and grid count, direction (long, short, neutral), and mode (arithmetic, geometric).

**What emerged was that all AI models adopted arithmetic grid mode with a neutral grid strategy, but showed clear differences in specific parameter execution such as price range and grid density:** Grok4 and ($100,000–$120,000), with the former deploying 50 grids (tighter spacing) versus only 20 for the latter; Gemini ranged from $105,000 to $118,000 with 50 grids; GPT-5 had the narrowest range at $105,000–$115,500 with the fewest grids (just 10, widest spacing); ($108,000–$112,000) with 20 grids.

**OKX platform market data showed BTC fluctuating between $103K and $116K during this period, with an overall pattern of oscillation and rise followed by a sharp downturn. It was precisely this "V-shaped reversal" that became the dividing line for the six AI models.** This precise range is critical for the analysis — it directly validates the core difference between this live test and conventional backtesting, and explains why some AI models "failed." Here are the live performance results:

Live Test Champion: Claude

Strategy Core: Moderate range, medium trigger density — balanced for both oscillation and trend phases, more stable

Claude clinched the title with a +6.18% cumulative return rate. Its success key was a "medium-wide, medium-dense" grid strategy — a configuration that served as the gold standard and was perfectly suited to BTC's oscillating market during this round, making it a reference case for balancing profitability and risk control in live trading.

Its grid range was set at $106K–$116K — neither as aggressive as , it steadily accumulated returns; even when the market sharply dropped, the $106K lower bound effectively contained drawdowns, outperforming all medium/narrow-range models. The moderate range with appropriate density ensured sufficient grid profits while keeping floating losses from position exposure minimal during the plunge.

Specifically, during the price rally, Claude avoided the grid inactivity that , steadily accumulating +7.90% in profit; when BTC plunged to around $103K during the sharp drop, Claude's lower bound of $106K left only a $3K gap, and its accumulated profits effectively cushioned the floating loss, keeping the drawdown under 5x leverage to just 1.72% — demonstrating excellent risk control.

Reliable Alternative: GPT-5

Strategy Core: Wide range with low density, higher per-trade profit, diluted risk through low position sizing

GPT-5 delivered a steady performance, ranking second with a +5.79% cumulative return — a reliable backup to Claude. Its strategy was proactive with a slightly higher risk appetite, tending to seize market opportunities, though its drawdown management fell short of Claude's. The returns curve rose in a stair-step pattern, growing faster but experiencing a larger pullback than Claude in the later stage (day 10). Overall efficiency was high, with profitability approximately twice the benchmark. GPT-5 currently stands as a steady, efficient alternative that balances returns and moderate risk, though drawdown management still has room for improvement.

The core feature of this model's grid strategy lies in low density with high per-trade returns. Compared to Gemini, although GPT-5's drawdown reached 2.65% — somewhat higher — the fewer grid count meant limited total position, diluting risk, while the $105K lower bound provided a cushion against sharp declines. During the oscillation phase, this strategy showed solid efficiency with cumulative returns reaching +8.44%. Compared to , GPT-5's lower bound is higher, giving it noticeably stronger resilience during price downturns. This strategy controls extreme risk exposure by limiting total positions while balancing returns and safety — a reliable alternative for those seeking efficiency with stability.

Most Conservative: Grok4

Strategy Core: Widest range with high density — ultimate defense, guaranteed zero grid gap

Grok4 represents the ultimate defense strategy. Compared to Qwen3, it completely sacrificed the offensive capability during the oscillating phase in exchange for the highest capital safety. The $100K lower bound ensures zero grid gap when BTC drops to $103K, and the high-density grid further spreads position risk, bringing the absolute drawdown to just 0.97%. Compared to , while both have similar efficiency, Grok4's returns curve is the smoothest with the lowest drawdown, making it the most conservative and robust choice — especially suited for users prioritizing capital safety.

There is also "Steadily Defensive " — its strategy core being the widest range with medium density, defense-first while balancing efficiency and zero grid gap. And "Outperforming Gemini" — its strategy core being a relatively wide range with high density, high-frequency micro-profits, spreading risk through broad coverage.

Notably, up with nearly identical returns, validating the logic that "range takes priority over density": under zero-grid-gap defense, the efficiency difference from medium density is neutralized — range width determines drawdown resilience, while density mainly affects returns curve smoothness and trigger frequency.

Gemini demonstrated how high-density strategies within moderately wide ranges enhance drawdown resilience: with the same lower bound as GPT-5, its high-density grid broadly distributed positions, effectively spreading the sharp-decline risk, bringing the drawdown to just 1.41% — noticeably better than GPT-5's 2.65%. This shows that high-density strategies can significantly improve stability and curve smoothness, making them a top choice for those seeking steady returns. Overview of strengths and weaknesses of all 6 AI model grid strategies (note: 's detailed strategy characteristics will be covered in the next section):

**Under the current setup, AI models achieving "collective survival" with positive returns rests on a solid logic:**

**During a market dominated by oscillating upward movement, all models successfully leveraged the "volatility equals profit" characteristic of their strategies to build a sufficient safety cushion. Even when extreme risk (sharp decline) occurred, this cushion was enough to withstand the erosion from floating losses, ensuring that all models ultimately maintained positive returns.**

"Fall from Grace": The Short-Term Trading Champion —倒数第一 in Contract Grid?

Let's first recap the results of Season 1 of NOF1's "AI Crypto Trading Live Arena": the Chinese-language models Qwen3 and , with ; all four U.S.-based models ended in the red.

This demonstrates that high-frequency trading carries higher risk: excessive trading incurs hefty fee drag on net worth, and a low win rate itself isn't可怕 — the key lies in risk management. The facts prove that even as complex AI strategies proliferate, simply holding Bitcoin (HODL) may still outperform most models.

One key takeaway is the stark contrast between the two experiment results: , but "fell from grace" in the grid strategy and ended up dead last — why?

In this strategy experiment, 's performance was the "biggest lesson" of the test. It once hit a peak monthly profit of +41.88% and a highest single-day return of 65.48U, but later suffered a massive 8.12% drawdown, bringing its final cumulative return to just 22.51U, ranking last.

**Its strategy core was:** Narrow range, high-frequency arbitrage — aggressively concentrated, only suited for oscillating markets. During the price rally, its tight range perfectly matched the oscillating market, enabling high-frequency arbitrage that pushed returns rapidly to a peak of +10.37%.

However, compared to other models, its $108K lower bound became the root cause of its collapse: when BTC sharply dropped to around $103K during the decline phase, the $5K grid gap left accumulated long positions completely exposed, and 5x leverage amplified the floating loss — profits were wiped out in an instant, with a day-10 drawdown of 8.12%, the largest among all models. This fully illustrates that while narrow-range strategies can generate profits quickly during oscillations, they lack defensive depth, are only suitable for tight-range oscillating markets, and are highly vulnerable when prices deviate significantly.

And in the previous "AI Crypto Trading Live Arena" Season 1, 's winning core was — timely strategy adjustment and market adaptation. As market volatility intensified in the later stage, , focused single-BTC full-position strategy with 5x leverage and precise stop-loss/take-profit settings, efficiently capturing rebound opportunities and achieving explosive净值 growth — validating its robustness in dynamic, uncertain environments (**the ability to maintain stable performance across different environments and market volatility levels without collapsing easily.**) and problem-solving capability. By contrast, 's conservative multi-dimensional evaluation, while excelling in risk control (highest Sharpe ratio), grew too slowly to fully capitalize on BTC's dominant trend, while the over-aggression of U.S.-based models like GPT-5 resulted in losses across the board.

One-sentence summary: ; its grid strategy failure stemmed from passive parameter flaws. Therefore, AI trading must match market conditions — avoid "one strategy fits all."

**The second key takeaway is:** In OKX and Ai Coin's historical market backtesting from July 25 to October 25, 2025, all six AI models showed zero grid-gap risk in BTC/USDT perpetual contract grid strategies with relatively stable returns. However, in this live test, multiple models experienced grid gaps or severe returns volatility. What does this difference reveal?

Seeing "zero grid gap" in backtests is often a false sense of security. Because the model is too familiar with historical data — it's been "fed" on it. But once in live trading, once the market breaks slightly below historical lows, strategies without defensive margins directly experience grid gaps. This also demonstrates that survival doesn't depend on clever algorithms — it depends on whether the range is wide enough and defenses deep enough. Don't worship "perfect backtests." A strategy that truly works is one that can survive the worst market conditions.

How to Beat the Market? Insights from the Two Experiment Results

The strategy tool used in this contract grid experiment was OKX Contract Grid (Ai Coin AI Grid). All AI models executed strategies based on this tool, ensuring consistency and fairness in trading execution. It is an automated trading tool supporting multiple modes including arithmetic, geometric, neutral, and long/short, with customizable parameters such as price range, grid count, and leverage. It is suited for capturing small-volatility returns in oscillating markets through batch position building and closing for arbitrage.

From this live test, AI's strategic capability matters, but the tool's role is equally critical. Claude's ability to stabilize returns wasn't just about good strategy design — it was largely thanks to the OKX grid tool, which automatically buys and sells within the range while managing risk, keeping the AI from getting stunned by a single pullback. , despite its more aggressive strategy, was protected by OKX's tool through batch position building and automatic stop-loss/take-profit, shielding its capital during high volatility and preventing catastrophic losses. In short, AI handles "what to do," while the grid tool handles "keeping you steady and executing the rules" — the combination is far safer and more likely to generate returns than relying on AI alone.

How to get more mileage out of AI + grid tools?

• Choose the right grid mode: If the market is oscillating, "neutral grid" is most stable; if the market has a clear direction, try "long/short grid" to follow the trend.

• Set reasonable range and grid count: Too narrow leads to excessive trading with fees eating into returns; too wide may miss swing profits.

• AI advises, but don't fully rely on it: AI can calculate parameters and point directions, but ultimately you must combine that with your own judgment of the market and tool characteristics.

• Backtest first, then go live: OKX grid tool has a paper trading feature, and Aicoin has historical backtesting — simulate first to see results, then live trading with more confidence.

High-risk strategies will always be the most unstable component of returns. Only by using the right strategies can AI's potential truly convert into tangible returns. Without risk control, even the smartest AI can go to zero overnight. So, don't blindly chase AI — the market is merciless, and AI pays tuition too. It can only be a tool; what truly supports you is risk management. In the next season, the hope is to see more mature, more stable AI strategies that truly understand risk control.

Disclaimer

This article may contain product-related content not applicable in your region. This article is only intended to provide general information and does not accept responsibility for any factual errors or omissions. This article represents only the author's personal views and does not constitute the views of OKX. This article is not intended to provide any advice, including but not limited to: (i) investment advice or investment recommendations; (ii) offers or solicitations to buy, sell, or hold digital assets; or (iii) financial, accounting, legal, or tax advice. Holding digital assets (including stablecoins) involves high risk and may be subject to significant price fluctuations or may even become worthless. You should carefully consider whether trading or holding digital assets is suitable for you based on your financial situation. For questions specific to your circumstances, please consult your legal/tax/investment professional. The information contained in this article (including market data and statistics, if any) is for general reference only. Although we have taken all reasonable precautions in preparing this data and these charts, we accept no responsibility for any factual errors or omissions expressed herein. © 2025 OKX. This article may be reproduced or distributed in its entirety, and may use excerpts of 100 words or less, provided that such use is non-commercial in nature. Any reproduction or distribution of the full article must prominently state: "This article is copyrighted © 2025 OKX, used with permission." Permitted excerpts must cite the article name and include attribution, e.g., "Article name, [author name if applicable], © 2025 OKX." Some content may have been generated or assisted by artificial intelligence (AI) tools. Derivative works and other uses of this article are not permitted.

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6 Major AI Grid Strategies Live Test: Claude Takes the Crown, All Models Post Positive Returns

"Fall from Grace": The Short-Term Trading Champion — Dead Last in Contract Grid?

How to Beat the Market? Insights from the Two Experiment Results

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