machines sharing compute

recent job receipts

client.pybefore

from openai import OpenAI

client = OpenAI(
    base_url="https://api.openai.com/v1",
    api_key="sk-proj-…",
)

resp = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user",
               "content": "hello"}],
    stream=True,
)

client.pyafter

from openai import OpenAI

client = OpenAI(
    base_url="https://console.cocore.dev/v1",
    api_key="cocore-7f3a2c…",
)

resp = client.chat.completions.create(
    model="mlx-community/Qwen2.5-0.5B",
    messages=[{"role": "user",
               "content": "hello"}],
    stream=True,
)

1job

You send a job

Your encrypted prompt heads out into the co-op. Run your prompt for a given model anywhere in the open network, or choose to keep your jobs private to only a trusted circle of co-op friends and their machines.

2attest + run

A member runs it

Someone picks up your job, runs it, then returns the result after signing with a key locked in the Secure Enclave that never leaves their hardware — proof of exactly who did the work, and that nobody touched it after.

3settle

Receipts, in the open

A receipt closes out the job — credits go to whomever who ran it, minus a small cut to a shared pot. Each month that pot splits back to members by how much they pitched in, so the cut cycles right back to the people running the network.

03 open by default

You don't have to take our word for it.

Every job writes a receipt anyone can verify on their own, without ever calling us. We can't inflate a balance, fake a payout, or quietly change the rules. And if you don't like how we run things, you can run the whole thing yourself — point your own copy at the same data and it lands on exactly the same numbers.

at://did:plc:jijw…lqrpec/dev.cocore.compute.receipt/3molljt5l3p2s

dev.cocore.compute.receiptsigned · did:plc:jijw…lqrpec

dev.cocore.compute.job@you.bsky.social

dev.cocore.compute.attestation@kira.bsky

dev.cocore.compute.settlement@cocore.dev