Gonka is a decentralized AI compute network. Developers run inference against hosted open-weight models through an OpenAI-compatible API and pay in the network's GNK token, while independent hosts contribute GPU capacity and are rewarded in GNK for serving that inference.
What's good about Gonka
- Inference is exposed through an OpenAI-compatible API, so existing client libraries work without rewrites
- Model catalog tracks recent open-weight releases from DeepSeek, Moonshot, and MiniMax
- Consensus design targets useful inference work rather than separate security computation
- Documented onboarding path for GPU owners who want to sell capacity into the network
- Protocol source, white paper, and tokenomics are published openly
Gonka does not publish public hourly pricing.
Contact the provider directly for a quote.
Billing & terms
- Token-metered inference
- Inference is paid per request in GNK; per-model rates are published in the network documentation rather than as USD hourly rates
- Host rewards
- GPU hosts earn GNK according to the amount and quality of compute they contribute to the network
- Support
- Documentation site with FAQ and error reference, Discord community, GitHub repository, and a vulnerability reporting process
Watch out for
- Usage is settled in GNK, which requires wallet setup, token acquisition, and exposure to token price movement
- No conventional GPU instance rental — developers buy inference, not machines
- Model availability and capacity depend on independent hosts rather than a single operator
- Hosts must post collateral and operate node infrastructure themselves
Features
- OpenAI-compatible inference API
- Developers send requests through an OpenAI-compatible endpoint and pay for usage in GNK
- Compute-as-consensus
- A transformer-based proof-of-work mechanism aims to direct nearly all participating hardware at AI inference rather than at separate security computation
- Permissionless hosting
- GPU owners register as hosts, post collateral, run ML nodes, and are rewarded based on the amount and quality of compute they contribute
- Open-weight model catalog
- Documented bootstrap procedures for hosting models such as DeepSeek, Kimi, and MiniMax across the network
- Self-hosted gateway option
- Developers can run their own gateway and broker setup instead of relying on a shared entry point
- Cross-chain transfers
- Ethereum bridge and IBC routes for moving GNK and USDT in and out of the network
- On-chain governance
- Protocol changes go through proposals, voting, and delegation by token holders
Getting started
Step 1
Create a Gonka account
Set up a wallet to hold GNK and sign network transactions
Step 2
Fund the wallet
Acquire GNK on Uniswap or bridge tokens in from Ethereum
Step 3
Connect an OpenAI-compatible client
Follow the developer quickstart to point an existing SDK at the network, or run your own gateway
Step 4
Or join as a host
Review the hardware specifications, post collateral, and follow the node setup guide to serve inference
Where this page's facts come from
- Profile
- Reviewed Jun 25, 2026
- Method
- How we collect and check prices
Frequently Asked Questions
Which models does Gonka serve?
Check the pricing table above for the models Gonka currently serves and their per-token rates.
How do I get started with Gonka?
Create a Gonka account, Fund the wallet, Connect an OpenAI-compatible client, Or join as a host
What are Gonka's main advantages?
Gonka's main advantages include: Inference is exposed through an OpenAI-compatible API, so existing client libraries work without rewrites, Model catalog tracks recent open-weight releases from DeepSeek, Moonshot, and MiniMax, Consensus design targets useful inference work rather than separate security computation, Documented onboarding path for GPU owners who want to sell capacity into the network, Protocol source, white paper, and tokenomics are published openly.
What are Gonka's limitations?
Gonka's main limitations include: Usage is settled in GNK, which requires wallet setup, token acquisition, and exposure to token price movement, No conventional GPU instance rental — developers buy inference, not machines, Model availability and capacity depend on independent hosts rather than a single operator, Hosts must post collateral and operate node infrastructure themselves.
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