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Akash Network Launches AkashML with fully managed AI inference on decentralized GPUs, offering fast, affordable deployment for open models.
Author: Akshat Thakur
Published On: Tue, 25 Nov 2025 13:38:11 GMT
November 25, 2025 — Akash Network Launches AkashML, delivering a fully managed AI inference service that runs open models on decentralized GPUs with one-click deployment and drastically lower costs than centralized cloud providers.
Akash Network Launches AkashML to simplify AI inference by offering a fully automated system for running open-source models on distributed GPUs. Unlike centralized services that often cost tens of thousands of dollars monthly, AkashML uses decentralized providers to dramatically reduce expenses while maintaining high performance.
The launch reflects Akash’s mission to bring powerful compute to developers, startups, and enterprises without reliance on traditional cloud monopolies.
AkashML introduces one-click deployments, automatic scaling, and pay-as-you-use pricing, eliminating infrastructure complexity. Developers can choose models, set configurations, and launch within minutes through the AkashML website.
The service supports leading open models such as DeepSeek, Llama, and Mistral, running them on vetted GPU providers. It also delivers sub-second inference latency, enhanced privacy through decentralization, and seamless integration with developer tools like Hugging Face.
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By decentralizing inference workloads, Akash Network Launches AkashML as a practical solution to high compute costs and vendor lock-in. The rise of AI has driven GPU shortages and skyrocketing cloud expenses, creating barriers for smaller teams. AkashML makes these capabilities accessible, positioning Akash Network as a foundational layer for AI development.
The ecosystem benefits include increased $AKT usage for transactions, higher demand for decentralized compute, and new opportunities for open-source model experimentation.
Akash Network Launches AkashML at a time when decentralized AI infrastructure is expanding rapidly. The service aligns with industry projections showing explosive GPU demand and a shift toward open, permissionless AI systems. By focusing on affordability, speed, and simplicity, AkashML distinguishes itself from collaborative or specialized inference networks.
As adoption increases, AkashML may integrate hybrid deployments, additional models, and cross-chain compute features to strengthen its position in decentralized cloud markets.
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