io.net

Position

io.net is the newest major entrant in this library's GPU compute coverage:

• Founded 2023 — younger than Render (2017), Golem (2017), and Akash (2020).
• Solana-based — IO token is an SPL token on Solana.
• Aggregator model: pulls GPU supply from diverse sources (Render, Filecoin, independent farms).
• AI/ML-first: built specifically for AI and machine learning workloads, not general compute or rendering.

Compared to other networks:

• vs. Render: Render is dedicated GPU rendering; io.net aggregates Render's supply plus other sources and focuses on AI/ML.
• vs. Akash: Akash is generic K8s containers; io.net is GPU-specific and ML-optimized.
• vs. Phala: Phala is TEE-confidential; io.net has no TEE component.
• vs. Bittensor: Bittensor is AI subnets with token incentives; io.net is raw GPU compute.

Architecture

Supply aggregation

io.net's innovation is aggregating GPU supply from multiple sources:

• Render Network contributors: Render providers can plug into io.net.
• Filecoin storage providers: Mining hardware with GPUs repurposed for compute.
• Independent data centers: Small and medium GPU clusters.
• Cryptocurrency miners: Ethash/Equihash miners with idle GPUs.
• Consumer GPUs: Individual providers contributing gaming GPUs.

This aggregator model means io.net doesn't need to bootstrap its own provider network from scratch — it taps existing GPU inventory via partnerships and integrations.

Verification and quality

Before any workload runs:

1. Proof-of-Work verification: GPU actually has the claimed compute.
2. Proof of Time-Lock: Provider commits to a lock-up period.
3. Staking: Providers stake IO as a performance bond.
4. 12-hour onboarding (first-time): GPUs, network, and system are stress-tested.

Platform components

The io.net ecosystem:

• IO Cloud: The core marketplace — dynamic scaling for AI/ML applications.
• IO Intelligence: AI infrastructure platform — pre-trained models and AI agents.
• IO Worker: Interface for GPU providers to contribute resources.
• IO Staking: Co-staking allocations tracking.
• IO Explorer: Real-time monitoring of compute usage and network activity.
• IO ID: Provider earnings tracking and withdrawals.

2025-2026: Solana migration

Notable 2026 development: io.net migrated fully to Solana, citing: - Instant GPU payments. - Smart contract automation. - Secure decentralized compute transactions. - Integration with the broader Solana DePIN ecosystem.

IO token

• Blockchain: Solana (SPL token)
• Utility: Payments, provider staking, governance
• Staking model: Providers stake IO as performance bond; slashing for underperformance.
• Reward distribution: IO tokens distributed to providers based on compute contributed.

Use cases

AI inference at scale

The primary io.net use case:

• LLMs serving on decentralized GPUs.
• Dynamic scaling across the aggregated network.
• Cost-competitive with hyperscalers for specific workloads.

ML training

Distributed training workflows across heterogeneous GPUs:

• Fine-tuning open-weights models.
• Batch training on aggregated compute.
• Integration with distributed training frameworks.

Inference via Render

io.net partners with Render to provide an inference pathway:

• Render focused on rendering.
• io.net provides AI/ML compute.
• Combined, they offer a broader GPU marketplace.

Comparison

Trade-offs

Strengths

• Aggregator model: Fast supply scaling by tapping existing GPU inventory.
• AI/ML optimization: Purpose-built for ML inference and training.
• Solana integration: Fast settlement, DePIN ecosystem alignment.
• Diverse sources: Combines render farms, miners, and data centers.
• 2025 production proof: Real AI workloads executed on the network.

Limitations

• No confidential computing: Provider sees all data. Not suitable for prompt privacy.
• Aggregator dependency: Relies on Render, Filecoin, etc. for supply. If partnerships falter, supply shrinks.
• No TEE story: Unlike Phala, no path to confidential AI inference.
• Newer than Render: Less track record in production GPU compute.
• Solana dependency: Has a blockchain dependency risk.
• Verification overhead: The 12-hour onboarding and verification may limit provider onboarding speed.

Attack surface

Recent developments (2024-2026)

Dell Technologies Partnership — Authorized Partner and Cloud Service Provider (June 2026)

io.net announced a partnership joining Dell Technologies Authorized Partner and Cloud Service Provider program. The collaboration:

• Merges io.net's decentralized GPU network with Dell's hardware and infrastructure.
• Go-to-market: demand generation and co-marketing.
• Positioned as bridging decentralized GPU power with enterprise-grade hardware infrastructure.
• Dell's channel relationships and enterprise salesforce give io.net access to customers that wouldn't find a crypto-native project organically.

Additional Partnerships (May-June 2026)

• Creator.Bid: Partnership to accelerate image model scaling using decentralized GPUs.
• Alpha Network: Partnership to establish a secure, decentralized environment for AI and Web3 applications.
• Mira Network: Strategic partnership for decentralized AI landscape.

2025 Production Proof — Real AI Workloads Executed

From io.net's 2025 Year in Review:

• Wondera: $2.48M savings vs AWS equivalent, 552,000 GPU hours, 96 GPUs (64 H100s + 32 H200s).
• Leonardo.Ai: Scaled from 14K to 19M users while cutting GPU costs 50%+ vs AWS.
• Platform claim: 30,000+ GPUs available, up to 70% lower cost than AWS.

Solana Migration (2026)

io.net migrated fully to Solana, citing: - Instant GPU payments. - Smart contract automation. - Secure decentralized compute transactions. - Integration with the broader Solana DePIN ecosystem.

IO Intelligence

Launched AI infrastructure platform — pre-trained models and AI agents on decentralized GPU.

Primary sources

• io.net — io.net
• Blog — io.net/blog
• Documentation — docs.io.net
• 2025 Year in Review — io.net/blog/2025-io-net-year-in-review
• Solana migration — io.net/blog/io-net-on-solana-the-place-for-depin-in-2026-and-beyond
• Messari report — messari.io/report/understanding-io-net-a-comprehensive-overview