Bittensor Subnet Investment Guide: Seizing New Opportunities in the AI Wave

In February 2025, the Bittensor network completed the Dynamic TAO (dTAO) upgrade, achieving decentralized resource allocation. Since then, the network has rapidly expanded to 118 active subnets, covering various fields of the AI industry and building a complete decentralized AI ecosystem.

The market performance is impressive, with the total market value of top subnets increasing to $690 million and staking yields maintained at 16-19%. The top 10 subnets account for 51.76% of network emissions, reflecting the survival of the fittest effect of the market mechanism.

Core Network Analysis (Top 10 Emissions)

1. Chutes (SN64) - serverless AI computing

Chutes uses an "instant start" architecture, compressing the AI model startup time to 200 milliseconds. Over 8,000 GPU nodes worldwide support mainstream models, processing over 5 million requests daily. Costs are 85% lower than AWS Lambda, serving over 3,000 enterprise clients. The current market value is 79M, making it a leading project in the subnet.

2. Celium (SN51) - hardware computation optimization

Focus on hardware-level computing optimization, maximizing hardware utilization efficiency through four major technology modules. Supports mainstream hardware, reducing prices by 90% and improving computing efficiency by 45%. Currently the second largest subnet in emissions, accounting for 7.28% of network emissions, with a current market value of 56M.

3. Targon (SN4) - Decentralized AI Inference Platform

The core is TVM( Targon Virtual Machine), which adopts confidential computing technology to ensure the security and privacy protection of AI workflows. The technical threshold is high, the business model is clear, and the income repurchase mechanism has been initiated.

4. τemplar (SN3) - AI Research and Distributed Training

Dedicated to large-scale distributed training of AI models, has completed training of a 1.2B parameter model. In 2025, it will advance large model training, with a parameter scale reaching 70B+. Current market value is 35M, accounting for 4.79% of emissions.

5. Gradients (SN56) - Decentralized AI Training

Reduce AI training costs through distributed training. Completed training of a 118 trillion parameter model at a cost of only $5 per hour. Over 500 projects are used for model fine-tuning, with a current market value of 30M.

6. Proprietary Trading (SN8) - Financial Quantitative Trading

Decentralized quantitative trading and financial forecasting platform, integrating LSTM and Transformer technologies to build multi-layer forecasting models. The website showcases the returns and backtesting data of different miner strategies, with a current market capitalization of 27M.

7. Score (SN44) - Sports Analysis and Evaluation

Focusing on sports video analysis, using lightweight verification technology to significantly reduce annotation costs. Collaborating with Data Universe, the AI agent has an average prediction accuracy of 70%. Targeting the $600 billion football industry, the market prospects are broad.

8. OpenKaito (SN5) - open-source text reasoning

Focusing on the development of text embedding models, supported by key players in the InfoFi field, Kaito. The project is still in its early stages and will soon integrate with Yaps, potentially expanding application scenarios.

9. Data Universe (SN13) - AI Data Infrastructure

Processing 500 million rows of data daily, with a total exceeding 55.6 billion rows. The DataEntity architecture offers features such as data standardization and index optimization. As a data provider for multiple subnets, it reflects the value of infrastructure.

10. TAOHash (SN14) - PoW mining

Allow Bitcoin miners to redirect their hashing power to the Bittensor network. In the short term, attract over 6 EH/s of hashing power, accounting for about 0.7% of the global total, providing a new source of income for miners.

Ecosystem Analysis

Bittensor's technological innovation has built a unique decentralized AI ecosystem. The Yuma consensus and dTAO upgrade enhance network efficiency, while the AMM mechanism enables market-based resource allocation. Inter-subnet collaboration supports distributed processing of complex AI tasks, and the dual incentive structure ensures long-term participation motivation.

Compared to traditional service providers, Bittensor stands out in terms of cost efficiency. However, it also faces challenges such as high technical barriers and regulatory uncertainties. The explosive growth of the AI industry presents a huge opportunity for Bittensor, with the global AI market expected to reach $1.77 trillion by 2032.

Investment Strategy Framework

Investing in the Bittensor subnet requires consideration of multiple dimensions such as technological innovation, team strength, market potential, competitive landscape, and token economics. It is advisable to diversify allocations across different types of subnets and adjust strategies according to the development stage.

The first halving in November 2025 will reshape the network economic landscape, allowing investors to position themselves in high-quality subnets in advance. The number of mid-term subnets is expected to exceed 500, and the increase in enterprise-level applications will drive the development of related subnets. In the long term, Bittensor may become an important component of the global AI infrastructure, with new business models continuously emerging.

The Bittensor ecosystem represents a new paradigm in the development of AI infrastructure, and its innovative vitality and growth potential deserve ongoing attention. Against the backdrop of rapid development in the AI industry, Bittensor and its subnet ecosystem provide investors with new opportunities to seize the AI wave.