The Morpheus network today: MOR at $2.467 (+1.5%), 26 providers serving 262 AI models

By Wren Okada, Decentralized AI Correspondent. Filed Wednesday 22 July 2026. Decentralized AI

The Morpheus network recorded 3,402 new AI inference sessions on July 22 while the MOR token traded at $2.467 . Twenty-six compute providers served 262 live models as 1.54 million MOR remained staked in open inference sessions . This daily activity occurred despite a weekly price decline of 0.3% for the native asset .

Network utilization metrics now define the value proposition more than spot price movements. The 1.54 million MOR staked in active sessions represents direct collateral for decentralized inference rather than passive speculation . Builder pools hold an additional 1.93 million MOR in total value locked to fund ecosystem development . These capital allocations secure access to 262 distinct models across 26 independent providers . The ratio of providers to models indicates that individual nodes serve multiple architectures simultaneously. Users verify these figures directly through the Base blockchain via the MorScan scanner . Price stability or volatility matters less than this verifiable link between staked tokens and delivered compute.

Specific model usage patterns reveal shifting demand within the broader session volume. The kimi-k2.7-code model processed 169 inference sessions in 24 hours from a single wallet . This represents a 412% increase over the prior day but lacks distribution across multiple users . Concentrated usage from one address suggests automated testing or batch processing rather than organic adoption. Broader user bases appear in other high-growth models. The glm-5.1-non-thinking model handled 106 sessions across eight distinct wallets with a 76.7% daily increase . Gemma-4-31b processed 83 sessions across six wallets and grew 93.0% day-over-day . GPT-5.4 saw 98 sessions from two wallets alongside a 69.0% gain . The glm-5.2:web model doubled its daily volume to 28 sessions across four wallets . These per-model breakdowns separate genuine multi-user demand from isolated volume spikes.

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