Solscan vs Nosana
Last updated: April 3, 2026
 |  | |
|---|---|---|
| Rating | (0) | (0) |
| Pricing | Freemium | Paid |
| Health | Healthy | Healthy |
| Chain | solana only | solana only |
| Open Source | ||
| Features | 8 features | 8 features |
| Upvotes | ▲ 1 | ▲ 1 |
| Twitter Followers | 57,126 | 58,593 |
| Categories | Analytics & Charts | Developer Tools, DePIN |
| Description | Free Solana block explorer — look up any transaction, wallet, token, or program with detailed analytics and holder data | Decentralized GPU compute marketplace for AI inference on Solana |
Pros & Cons
Solscan
- Most comprehensive and reliable Solana block explorer
- Default transaction verification tool linked by wallets and dApps
- Labeled accounts make it easy to identify known entities on-chain
- Pro API provides structured data access for developers
- Fast loading and responsive interface even during high network activity
- Pro API requires paid subscription for higher rate limits
- Advanced analytics features are less deep than specialized platforms like Birdeye
- Mobile experience could be more optimized for smaller screens
- Historical data queries can be slow for very active accounts
Nosana
- Significantly cheaper GPU compute compared to centralized cloud providers for inference
- Targets the largest segment of AI compute spending (inference = 80-90% of total)
Solscan vs Nosana: Which Should You Choose?
Overview
Solscan Solscan is the most widely used blockchain explorer for Solana, providing comprehensive tools for inspecting transactions, accounts, tokens, and on-chain programs. It serves as the default reference p... Nosana Nosana is a decentralized GPU compute marketplace on Solana that connects AI developers who need GPU resources with node operators who have idle GPU capacity. The protocol focuses specifically on AI i...
Community Ratings
Both Solscan and Nosana hold similar community ratings, suggesting users find comparable value in each. Your choice should come down to specific features, pricing, and ecosystem fit rather than overall score.
Pricing & Value
Solscan uses a freemium model — Free explorer with basic analytics. Pro plans start at $39/month for advanced features and API access., while Nosana is paid — Pay-per-job GPU compute pricing. Rates vary by GPU type and job duration. Typically 50-80% cheaper than AWS/GCP inference. Payment in NOS tokens..
Key Features
Solscan offers 8 features including Comprehensive transaction inspection with instruction-level detail, Token analytics with supply, holders, transfer history, and metadata, Account explorer showing balances, tokens, staking, and DeFi positions, and 5 more. Nosana counters with 8 features including Decentralized GPU marketplace matching AI workloads with available compute nodes, Focus on AI inference — optimized for running trained models in production, Support for consumer GPUs to enterprise A100/H100 data center hardware, and 5 more. The right choice depends on which specific features matter for your use case — check the individual review pages for full breakdowns.
Reliability & Health
We monitor both tools around the clock for uptime, SSL validity, and response times. Solscan currently has a healthy health status with 100.0% uptime over the last 30 days. Nosana is rated healthy with 100.0% uptime. For tools you rely on daily — especially trading bots or wallets — uptime and speed are non-negotiable.
Strengths
Solscan's key strengths include most comprehensive and reliable solana block explorer, default transaction verification tool linked by wallets and dapps, labeled accounts make it easy to identify known entities on-chain. Nosana stands out for significantly cheaper gpu compute compared to centralized cloud providers for inference, targets the largest segment of ai compute spending (inference = 80-90% of total), growing gpu supply from diverse node operators provides competitive pricing. On the flip side, Solscan's weaknesses include pro api requires paid subscription for higher rate limits, while Nosana's main drawback is decentralized compute has inherent latency overhead compared to dedicated data center deployments.