(3/4) Every model we add to the IDLE network makes
$IDLE more deflationary.
Here's why.
IDLE routes inference jobs across three compute layers - local nodes running open-source models, NVIDIA NIM serving large GPU-optimized models, Mistral AI for sovereign European inference, and now Kimi K2.6, the 1 trillion parameter model that ties GPT-5.5 on coding benchmarks at a fraction of the cost.
Every time a local node completes a job, 15% of the fee auto-swaps to
$IDLE via Jupiter and burns it permanently. As the model catalog grows, more demand flows to the network, more jobs route to local nodes, and more
$IDLE gets burned every hour.
The flywheel is simple: more models = more demand = more jobs = more burns = less supply.
74,467 active nodes. 101,370 on-chain transactions. Every integration compounds that. NVIDIA NIM. Mistral. Kimi K2.6. Each one expands the catalog, attracts more demand, and accelerates the burn rate.
The DePIN sector is $9-10 billion in market cap. IDLE is sub-$300K FDV with real revenue, real burns, and a model catalog that now includes the most capable open-source models on earth.