Truly open AI, powered by AI Bitcoin.
Ambient is a Solana-compatible (SVM), proof-of-work Layer 1 blockchain that turns decentralized GPU compute into one continuously improving, open-weights foundation model, then verifies that model's outputs. It delivers the privacy, censorship resistance, and cost profile of crypto AI with the speed, uptime, and reliability developers expect.
Why Ambient exists#
Two problems motivate the network. The first is that closed AI is powerful but risky: a centralized provider can change model behavior, raise prices, restrict access, censor outputs, or compete with the applications built on top of it. The second is that current crypto-AI networks underdeliver. Proof-of-stake model "marketplaces" have low utilization, stale models, inconsistent quality, and limited incentives for new compute to join; verified inference has not been practical at these scales (ZK approaches carry roughly 1000x overhead, optimistic approaches carry asymmetric risk); and decentralized training has been too inefficient to be usable.
Ambient's response: one large model (600B+ parameters) and its fine-tunes, verified inference with less than 0.1% overhead, training designed to run efficiently across the network, and a proof-of-work scheme where the work itself is useful inference.
The single-model thesis#
Rather than a marketplace of many models, Ambient concentrates the network on that one model. Users avoid a paradox of choice, agents avoid depending on models of unknown provenance, and miners get steady utilization instead of paying constant model download-and-load costs. Ambient's mission, from the Ambient Litepaper:
an AI secured blockchain ten times more efficient than incumbent systems with built-in privacy and censorship resistance that runs a single, huge, highly performant, auditable, and transparent model (and its fine tunes) at low latency…
Compared to Bitcoin's proof of work#
Ambient frames itself as the next step for proof of work: keep the security model, change what the work produces. Bitcoin's miners compute hashes that have no value outside securing the chain; Ambient's miners run inference that somebody wanted anyway.
| Bitcoin | Ambient | |
|---|---|---|
| Network security | Proof of work | Useful proof of work |
| Hash power potential | ASICs, steady | GPUs, exponentially increasing |
| What the work is | Hashing | AI inference on one large model |
| Throughput target | ~7 TPS | ~65,000 TPS |
| Deflationary bet | Fixed supply | AI demand increases |
The throughput figure is the SVM-derived design target, not a measured testnet number.
How Ambient works#
- Proof of Logits (PoL). Verified inference is the work. During generation, the model's internal logits (pre-softmax scores) form a unique fingerprint of its computation. Miners commit hashed progress markers of these logits; a validator can check a response by recomputing just one token and comparing hashes. Expensive to generate, cheap to validate. See Proof of Logits.
- Continuous PoL and leader election. The network continuously measures validated work from inference, fine-tuning, and training. Leaders are elected based on recent logit stake (LStake), contribution to useful work, measured rather than a locked token stake, while transaction ordering stays Solana-fast and non-blocking.
- Query auction and quality of service. Users and agents post requests with a desired latency and price; miners bid to serve them, each posting a deposit that is returned when the query completes on time and forfeited if it does not. Validators are selected with LStake-weighted randomness. See Network architecture.
Where the network stands today#
The paid API is live at api.ambient.xyz, the chain is running as a testnet,
and mining onboarding runs in curated waves.
Keep reading#
- Proof of Logits: the verification mechanism in depth
- Network architecture: roles and the life of a request
- Tokenomics: how the reward design works
- Get started: make your first API request