STRATEGY · CONTROL · EXECUTION
AlphaNet vs Bitsgap
Trained model strategies or a configurable bot portfolio?
AlphaNet focuses on developed quantitative and deep-learning model strategies. Bitsgap combines bot types, a trading terminal and an AI Assistant that helps users create and manage bot portfolios.
Reviewed 21 October 2026 · Published by AlphaNet
The comparison, side by side
Compare the actual strategy and operating workflow. Product availability can vary by venue, account and plan.
| What to compare | AlphaNet | Bitsgap |
|---|---|---|
| Core offering | Developed quantitative and deep-learning model strategies. | GRID, DCA and related bot types, smart trading tools and AI-assisted bot portfolios. |
| Your main decisions | Choose an available strategy, asset and allocation, then monitor its behavior. | Choose a supported venue and bot approach, settings, investment amount and risk preferences. |
| Role of AI | Trained models are part of the strategy’s trading decisions. | The AI Assistant helps select and manage bot portfolios; individual bot types have their own trading mechanics. |
| Trading venue | Hyperliquid perpetual futures through your own account. | Supports Hyperliquid DCA Futures and other exchange connections. Bot and AI-feature availability vary by venue. |
| Permissions and funds | An agent wallet can place trades but cannot withdraw. AlphaNet never receives or holds your funds. | Bitsgap states that it connects via exchange APIs and cannot withdraw the funds in the connected account. |
| Platform fees | No AlphaNet fees during the promotional period. Hyperliquid protocol fees still apply. | Subscription plans determine included tools and limits; exchange fees remain separate. |
| How to assess results | Review strategy-level research, testing and live periods, drawdown and execution costs. | Review the selected bot mechanics, parameters, market regime, backtests and live results after costs. |
WHERE THE TRADING DECISION COMES FROM
Start with the strategy.
AI can play different roles inside a trading product. AlphaNet’s model strategies use quantitative research and deep learning within their trading process. Bitsgap’s AI Assistant supports the construction and management of bot portfolios. Calling both products “AI” does not explain how trades are decided; the underlying mechanics and evidence are what matter.
On AlphaNet, you choose a developed strategy and allocate USDC. With a Bitsgap GRID bot, the selected market and grid settings determine how the bot places orders across a price range. Its AI Assistant can reduce configuration work, but the bot type and its operating assumptions remain important to the result.
Explore AlphaNet research and documentationWHEN TO EXPLORE ALPHANET
You want developed strategies.
You prefer selecting a researched strategy, profile and allocation over defining each trading rule. Compare Hackworth, Archimedes and Archimedes Pi, subject to current access and availability.
Explore markets and strategy historyWHEN TO EXPLORE BITSGAP
You prefer this workflow.
You want grid, DCA or related bot workflows, multi-exchange tools, and assistance with selecting or managing bot configurations.
Questions about AlphaNet vs Bitsgap
Does Bitsgap have AI features?
Yes. Bitsgap offers an AI Assistant for bot-portfolio creation and management. This page distinguishes that role from AlphaNet’s developed model strategies; it does not claim Bitsgap has no AI.
Does choosing a bot remove strategy decisions?
No. The bot type, selected market, settings and allocation all affect behavior. Assistance can simplify setup, but you should still understand how the selected approach trades.
What should I compare besides a headline return?
Compare the exact trading approach, dates, live versus simulated evidence, drawdown, account permissions and all relevant costs. Different bot setups and model strategies can have very different exposure.
CONTINUE YOUR COMPARISON
Choose the approach
that fits your trading.
Explore AlphaNet’s strategies, research and dated market data before choosing an allocation.
For a wider perspective, explore how much the AI decides in each bot.
Published by AlphaNet using official product descriptions reviewed on 21 October 2026. This comparison describes workflows, not a ranking of returns. Trading involves risk; past performance does not guarantee future results.