BitMind PriceSN34

What is BitMind (SN34)?

BitMind (SN34) operates on Bittensor Subnet 34. It began in 2024 as a decentralized deepfake detection network and, in October 2026, Subnet 34 transitioned to Yugos, an AI inference router that selects the model, provider, and reasoning effort for each request. The project positions itself as "the trust layer for enterprises," focused on verifying the authenticity of digital content before AI systems act on it. BitMind combines blockchain and artificial intelligence to detect AI-generated content across images, videos, and audio, aiming to stop fake media before it spreads. BitMind states that its detection achieves 95% accuracy on real-world deepfakes with sub-second latency and is deployed across more than 100 countries. Founded in 2024, BitMind operates as Bittensor's premier AI-generated content detection subnet. Its token, SN34, has a maximum supply of 21,000,000 and a self-reported circulating supply of 1,219,745 SN34.

Key Specifications & Tokenomics

• Name: BitMind
• Ticker / Symbol: SN34
• Blockchain / Network: Bittensor (Subnet 34)
• Contract Identifier: 34 (Bittensor)
• Category: AI & Big Data, Bittensor Ecosystem, Bittensor Subnets
• Max Supply: 21,000,000 SN34
• Total Supply: 1,219,745 SN34 (self-reported; the registry circulating-supply field shows 0)
• Self-Reported Circulating Supply: 1,219,745 SN34
• Founded: 2024
• Founder: Ken Jon Miyachi
• Listing Date: June 20, 2025
• Official Website: https://bitmind.ai/
• GitHub: https://github.com/BitMind-AI/bitmind-subnet
• X (Twitter): https://twitter.com/BitMindAI
• Explorers: taostats.io

Who created BitMind?

BitMind was founded in 2024 by Ken Jon Miyachi, who serves as Co-founder and CEO. Ken Miyachi appeared on the "Bittensor Revenue Search" podcast to discuss his work in deepfake detection using computer vision technology. Dylan Uys serves as Co-founder and Head of AI at BitMind. Canh Trinh serves as Head of Engineering, with prior experience at Axelar, JPMorgan, and Deutsche Bank. The team is described as US-based. The team brings experience from organizations including Amazon, NEAR Foundation, ViaSat, JP Morgan, and Deutsche Bank. The project is developed and maintained by BitMind-AI, a team focused on decentralized AI infrastructure and content verification. Note: a third-party company profile lists a different founder and a Cayman Islands location for a company named BitMind; this conflicts with the co-founders identified by the project's own materials and is treated as ambiguous.

How does BitMind work?

BitMind operates through its Generative Adversarial Subnet (GAS), a mechanism inspired by Generative Adversarial Networks. Detectors and generators compete in a dynamic loop: detectors sharpen their ability to identify synthetic media while generators push to create more convincing fakes. This adversarial process drives continuous improvement in detection tools and generates training data. The subnet runs two parallel tracks on Bittensor Subnet 34. Discriminative Mining involves submitting media-provenance classifiers for image, video, and audio, scored by a geometric mean of normalized MCC and Brier performance. Generative Mining involves running a server that generates synthetic media on demand, with rewards based on valid content and the ability to fool discriminators. Models must be submitted in Safetensors format, and datasets refresh weekly with GAS-Station data.

What makes BitMind unique and valuable?

BitMind launched as a deepfake detection subnet built on a self-evolving detection system, which uses GAN-style miner competition to generate hard deepfakes and train top detectors in real time. In October 2026, Subnet 34 moved to Yugos, an AI inference routing product. Unlike static AI safety solutions that wait months for researchers to develop defenses, BitMind's adversarial approach ensures detectors evolve as fast as the threats they face. BitMind states that its detection achieves 95% accuracy on real-world deepfakes with sub-second latency and production-grade availability backed by contractual SLAs. BitMind also emphasizes enterprise security, offering SOC 2 Type II compliance, GDPR and CCPA alignment, TLS 1.3 encryption, zero data retention, and ephemeral container processing. The project supports three modalities—image, video, and audio—with independent scoring, and provides both consumer-facing apps and enterprise-grade APIs.

What is BitMind used for?

SN34 serves as the native token of the BitMind subnet on Bittensor, used to incentivize miners and validators participating in the network. Miners earn rewards for submitting accurate detection models or generating synthetic media that helps train discriminators. Validators evaluate and score miner submissions. Revenue from developers using the API is intended to fund buybacks of the subnet's alpha token. Beyond mining, BitMind's technology powers practical applications including the BitMind ID verification tool, the "AI or Not?" mobile app, a Chrome extension for verifying content while browsing, and an enterprise REST API offering 100 free scans per month. These tools serve individuals, teams, and regulated industries such as financial services, government, and media platforms.

How Is the BitMind ecosystem developing?

The BitMind ecosystem has expanded through product launches and strategic partnerships. The BitMind Chrome Extension reported 8x user growth and 3x API requests in a two-week period; the project states it maintained the highest detection accuracy in the market. The "AI or Not?" mobile app provides on-the-go verification, and BitMind ID offers image authenticity checking. In October 2026, Subnet 34 transitioned to Yugos, an AI inference router that decides, for every request, which AI model, which provider, and how much reasoning effort to use. Developers send requests to a single OpenAI-compatible API, and Yugos picks the option giving a good answer at the lowest cost and in the least time. BitMind has received coverage from Binance Square and SimplyTao, and maintains an active GitHub repository with 1,072 commits. In July 2026, BitMind published a 16-page thesis on the future of deepfake detection, introducing a continuously evolving AI system that adapts to new threats through Bittensor's competitive network. Enterprise solutions include custom SLAs, on-premise deployment, white-label options, and dedicated account management.

How to mine BitMind?

Mining BitMind (SN34) involves participating in one of two tracks on Bittensor Subnet 34. Discriminative miners submit media-provenance classifiers for image, video, or audio detection, with one model per hotkey. Models must be in Safetensors format; ONNX submissions are not accepted. Rewards are based on accuracy and calibration. Generative miners run a server that generates synthetic media on demand, earning base rewards for valid content plus multipliers for fooling discriminators. Installation involves cloning the BitMind-AI/bitmind-subnet repository, running the install script, and using the gascli tool to start validator or miner services. Discriminative mining significantly reduces the capital required compared to earlier versions that required GPU hosting. Miners can check benchmark performance through authenticated commands filtered by modality or vertical.

How to keep your BitMind Coin safe?

Securing SN34 tokens requires standard cryptocurrency safety practices. Store tokens in a reputable wallet that supports Bittensor-based assets, and consider hardware wallets for significant holdings. Never share private keys or seed phrases, and verify all transaction details before confirming. Because SN34 operates on the Bittensor network, use official explorers like taostats.io to monitor balances and activity. Be cautious of phishing attempts, fake websites, and unsolicited offers. Enable two-factor authentication where available and keep software updated. BitMind's enterprise-grade security features, including TLS 1.3 encryption, zero data retention, and in-memory processing with automatic cleanup, apply to its detection services, but individual token security remains the holder's responsibility. Always conduct thorough research before interacting with any platform or service.

Risks and uncertainties

SN34 is subject to market risk, and its price fluctuates with the market. Regulatory treatment of crypto assets and of AI-generated media varies by jurisdiction and may change. The project also carries technical risk, including the possibility that detection models fail to keep pace with new generative techniques. These factors should be weighed alongside the project's stated capabilities.