brain
Network live · 12,842 GPUs online SIM

The crowd
is the GPU.

Your browser becomes part of an AI supercomputer. Contribute verified compute. Earn from real creator revenue.

Contribute GPU→Use the network
JOB #918282 assignedEXAMPLE
INSIDE NODE 8A21 · EXAMPLE JOB
GPUS ONLINE12,842■MEMORY68.4 TB■REQ/S482■INFERENCES 24H4.82M■QWEN 32B4,821 nodes■DEEPSEEK DISTILL2,184 nodes■EMBEDDINGS1,821 nodes■VISION884 nodes■CREATOR REWARDS 24H$18,482■PAID TO GPUS 24H$14,201■UPTIME99.91%■BRAIN$0.001842■SIM · DEMO DATA
GPUS ONLINE12,842■MEMORY68.4 TB■REQ/S482■INFERENCES 24H4.82M■QWEN 32B4,821 nodes■DEEPSEEK DISTILL2,184 nodes■EMBEDDINGS1,821 nodes■VISION884 nodes■CREATOR REWARDS 24H$18,482■PAID TO GPUS 24H$14,201■UPTIME99.91%■BRAIN$0.001842■SIM · DEMO DATA

One request, traced.

From API call to paid contributors. Scroll to step through it.example trace

  1. 01Request
  2. 02Gateway
  3. 03Router
  4. 04Split
  5. 05Nodes
  6. 06Verify
  7. 07Merge
  8. 08Response
trace · job #9182821 events · Request
  1. 0.000sPOST /v1/chat/completions model=brain/auto priority=cheap
  2. ▍

A developer sends one request

POST /v1/chat/completions with model brain/auto. Same shape as the OpenAI API, so existing SDKs work unchanged.

01 / 03

One datacenter GPU.

The usual way to serve AI: a single 80 GB accelerator in a rack, rented by the hour.

GPUs
1
Memory
80 GB

1 point = 1 node · orange = serving a request now

Live topology

The same network as a routing graph: requests enter, split across device classes, execute, and merge. Green markers are real browsers connected right now.

Live topology
482 req/s0 liveSIM
    GPUs onlineSIM
    12,842
    Available memorySIM
    68.4 TB
    Inferences todaySIM
    4.82M
    Creator rewards todaySIM
    $18,482
    Paid to compute providersSIM
    $14,201
    Avg cost / 1M tokensSIM
    $0.XX
    Network uptimeSIM
    99.91%
    Contribute

    Your laptop
    is a node.

    No install, no driver, no CLI. Open a tab, let it measure your GPU, and join. The server issues a challenge only a real GPU can answer in time, then starts sending verifiable work.

    1. 01DetectReads exactly what WebGPU exposes. Anything it can’t see is labeled unavailable, never guessed.
    2. 02BenchmarkA WGSL kernel on your GPU. Score comes from the server’s clock, not yours.
    3. 03JoinYour node appears in the topology and starts receiving jobs within seconds.
    Contribute GPU→See live jobs
    BRAIN · NODE
    STATUS01/06
    DEVICE DETECTED
    WebGPU · READY
    adapter: apple · metal-3
    preview of the join sequence · values illustrative
    Rewards

    What your
    GPU earns.

    Rewards are paid for verified compute, from creator fees and inference sales. Holding tokens raises your multiplier, up to a cap. Holding alone earns nothing.

    Measure your GPU→How rewards work
    Your GPU19,500 score SIM
    Test your actual GPU

    About one second. Runs a real WGSL kernel; the server times and verifies the result.

    Presets are network median scores SIM · only the measured score is real

    Hours online per day20 h
    Token holdings2,500,000 BRAIN · 0.25%
    Estimated rewardEST
    $2.46/ day
    7 days $1730 days $74
    Where it comes fromcompute $1.48 · token boost +$0.98
    Token multiplier1.66× of 3× max
    1× no tokens3× cap
    Same GPU, no tokens
    $1.48 / day
    Same tokens, no GPU
    $0.00 · rewards require verified compute
    Contributor pool today
    $14,201 SIM

    Estimate using the production reward formula against a simulated network. Actual rewards depend on realized creator fees and inference sales, and on the verified compute of all other contributors. Not a guarantee of earnings.

    Inference

    Use the
    crowd.

    An OpenAI-compatible API in front of the network. The router sends each request where it runs best: the browser pool when the model fits, a cloud fallback when it doesn't.

    • brain/autoAutomatically chooses the cheapest execution path that satisfies the request.
    • brain/qwenDistributed Qwen-class inference across the browser pool.
    • brain/codeCoding-optimized inference on distilled reasoning models.
    • brain/embedDistributed embeddings. Small model, highly parallel, browser-native.
    Open playground→API reference
    POST /v1/chat/completions
    curl https://brain.network/v1/chat/completions \
  -H "Authorization: Bearer $BRAIN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "brain/auto",
    "messages": [{"role": "user", "content": "Explain this contract"}]
  }'

    Drop-in for OpenAI SDKs: set base_url to your BRAIN endpoint. Examples →