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Choose a blockchain only when your AI agent needs shared state, programmable settlement, public auditability, or coordination between parties that do not share a trusted operator. If the agent only performs private inference or calls centralized APIs, a conventional backend is usually simpler and cheaper.
For a blockchain-based agent, decide in this order: define the trust model, map the payment flow, limit the agent’s authority, benchmark the real workload, then select the network and tooling your team can operate securely. Ethereum and Solana both document agent-oriented capabilities, but the available sources do not establish an independent, controlled head-to-head performance winner.
Does your AI agent need a blockchain?
“Which blockchain should I use for an AI agent?” is the wrong first question. The first question is whether a blockchain solves a requirement that a database, API gateway, or managed payment service cannot.
A blockchain can provide a shared state that several organizations can verify, programmable settlement, a public audit trail, and coordination without one party controlling the entire system. Those properties matter when an agent acts across organizational boundaries, pays an unfamiliar service, publishes claims that others must verify, or participates in an open marketplace.
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They are not automatically useful for every agent. An internal support agent, a private document summarizer, or a workflow bot that calls ordinary centralized services may gain little from transaction fees, wallet management, confirmation delays, contract risk, and chain-specific operations.
Use a chain when the requirement is genuinely onchain
- Shared state: Multiple parties need the same authoritative record of ownership, balances, permissions, jobs, or service results.
- Programmable settlement: Payment or escrow must execute according to contract rules rather than a single operator’s database logic.
- Public auditability: You need an independently inspectable history of agent actions or commitments.
- Inter-organizational coordination: Participants do not want to trust one company to maintain the registry, payment ledger, or task state.
- Verifiable computation claims: You need a mechanism to validate an inference or task result, not merely a log saying that a model ran.
Keep the critical path offchain when it does not need consensus
Model inference, prompt handling, private user data, retrieval indexes, and high-volume intermediate steps are often better handled offchain. Put only the state, commitments, payments, permissions, or proofs that other parties must verify onchain. This hybrid design can reduce cost and latency while retaining a verifiable settlement layer.
Ethereum.org presents verifiable inference, payments, wallet controls, and registries as possible agent use cases. It does not claim that every agent needs a blockchain. Its overview also describes the area as experimental, so treat the architecture as something to validate against your own requirements rather than as a default deployment pattern.
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Write a trust statement before comparing networks. Specify which claims a client, counterparty, or auditor must be able to check:
- Who the agent is and which owner or organization controls it.
- Whether the agent has a history of acceptable behavior.
- Whether a task was executed according to an agreed procedure.
- Whether a model inference or result can be independently validated.
- Whether a proposed transaction is authorized, within budget, and still valid.
These are different functions. A wallet address can identify an agent without proving that its model is reliable. A reputation score can summarize feedback without proving that a particular output is correct. A transaction signature can authorize a payment without proving that the agent chose the right recipient.
Identity, reputation, and validation are separate layers
ERC-8004, the Ethereum Improvement Proposal titled “Trustless Agents,” proposes separate identity, reputation, and validation registries. Its scope explicitly excludes payments. That separation is useful when designing your system: select or build a payment mechanism independently from the records used to identify agents, collect feedback, or validate work.
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The proposal describes several possible validation approaches, including client feedback, stake-secured re-execution, zero-knowledge machine learning (zkML), and trusted execution environment (TEE) oracles. These approaches have different cost, latency, privacy, and trust assumptions. A registry entry or reputation signal is evidence for a decision; it is not proof that an agent is safe.
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What Solana’s Agent Registry provides
Solana’s Agent Registry documentation describes onchain identity metadata, reputation signals, and hooks for independent validation, with an interoperability goal. Read this as a description of the registry’s design and intended capabilities, not as independent evidence of adoption, security, or effectiveness. Ask which registry fields your application will actually consume, who can update them, and how stale or malicious entries are handled.
Choose the payment model before choosing the network
Agent applications often need to pay for compute, data, APIs, tools, or other agents. Payment design is more specific than “supporting crypto.” Define the complete path: client, service, token, authorization, settlement network, facilitator, refunds, and failure handling.
Per-request payments
A one-time charge fits a discrete action such as a single data query, image generation request, or tool invocation. The client should know the amount and recipient before authorizing the request, and your service needs a clear response for rejected, expired, duplicated, or partially completed payments.
Metered sessions
A long-running agent may consume resources over a session. A capped metered authorization can avoid signing every small request while limiting the maximum exposure. Define the cap, measurement unit, expiration, settlement interval, and what happens if usage data and the client’s view diverge.
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MPP and x402 are not interchangeable labels
Solana’s agentic-payments documentation says that MPP and x402 use different headers and data models. MPP supports one-time charges and capped metered sessions. x402 supports payment schemes such as exact and upto, with support varying by network and client. The documentation’s guidance is to choose based on the payment model and interoperability your service needs, not only the shared HTTP 402 status code.
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| Decision | Questions to answer | Why it affects chain selection |
|---|---|---|
| Charge pattern | Is each request paid separately, or is usage metered within a capped session? | Different protocols and clients model authorization and settlement differently. |
| Token and currency | Do you require a stable-value token, a native asset, or both? | Token availability, wallet support, and settlement paths differ by network. |
| Client compatibility | Which SDKs, headers, wallets, and facilitators can your users run? | A protocol name does not guarantee support in your exact client and target network. |
| Failure behavior | What happens after timeout, duplicate submission, partial work, or a service outage? | Retries and reconciliation must be designed around the chain’s transaction and confirmation behavior. |
| Refunds and disputes | Can the service reverse a charge, or must it use escrow or an application-level credit? | Settlement finality does not by itself provide a consumer refund mechanism. |
Ethereum.org describes x402 payments for compute, data, and API calls using stablecoins on Ethereum and layer-2 networks. Verify support for the exact network, token, wallet, client, and facilitator you intend to deploy. A protocol reference alone is not a compatibility guarantee.
Bound the agent’s authority instead of handing over a private key
An autonomous agent should not have unrestricted control over funds or contracts. Design authority as a policy that can be inspected, limited, revoked, and escalated to a human.
Controls every deployment should define
- Permitted operations: Specify which contracts, methods, assets, and transaction types the agent may use.
- Spending caps: Set per-transaction, per-session, daily, and total budget limits where appropriate.
- Allowlists: Restrict recipients, service endpoints, tokens, and contract addresses.
- Expiry: Make delegated permissions and session keys expire automatically.
- Revocation: Provide an operator-controlled emergency disable path and test it.
- Human escalation: Require approval for unusual recipients, high-value actions, policy changes, or ambiguous requests.
- Monitoring: Alert on spend velocity, repeated failures, policy violations, unusual destinations, and changes to agent configuration.
- Recovery: Document how to rotate credentials, pause contracts, recover assets, and restore service after a compromised host or provider.
Ethereum.org documents smart-account capabilities such as spending limits, whitelists, session keys, and granular permissions. These are risk-reduction mechanisms, not a guarantee that the wallet, contract, agent host, model, or external service will behave safely.
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What ERC-8196 proposes
ERC-8196, “AI Agent Authenticated Wallet,” was created on March 14, 2026. It proposes a policy-bound wallet interface in which a transaction is executed only when accompanied by cryptographic proof that the action complies with an owner-defined policy. The proposal discusses risks including unsafe credential delegation, host manipulation, and replay or timing vulnerabilities.
ERC-8196 is a standard proposal, not evidence of universal implementation. Adopting a policy interface would not remove the need to secure the wallet, validate policy inputs, protect the agent host, monitor transactions, and maintain a human recovery path.
Compare Ethereum and Solana against your workload, not a slogan
Ethereum and Solana both publish material aimed at agent applications. The available sources do not provide an independent, controlled head-to-head benchmark of their performance, security, ecosystem maturity, or developer experience. Treat ecosystem documentation as a statement of available features and claims, then measure your own application.
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| Comparison axis | Ethereum-oriented questions | Solana-oriented questions | Evidence limit |
|---|---|---|---|
| Trust and registries | Can identity, reputation, and validation records use the registry patterns described by ERC-8004? | Do the Agent Registry’s metadata and validation hooks match your interoperability needs? | Registry design does not prove adoption or agent safety. |
| Payments | Does your target Ethereum or layer-2 network support the chosen x402 flow, token, wallet, and facilitator? | Should your service use MPP’s one-time or capped-metered model, or an x402 scheme supported by your client and network? | Support varies by network, client, and implementation. |
| Account controls | Are smart-account permissions, session keys, allowlists, and spending limits available in your stack? | Which wallet and program controls provide equivalent policy boundaries? | Feature availability must be checked in the exact wallet and contracts you deploy. |
| Performance | What confirmation, fee, and retry behavior does your selected network produce under your workload? | Can the selected network meet your latency, throughput, and cost targets under measured conditions? | No independent cross-chain benchmark is established by the cited material. |
| Operations | Which contract libraries, RPC endpoints, indexers, wallets, testnets, and incident procedures can your team support? | Which SDKs, RPC and indexing services, payment clients, and operational tools can your team support? | Official pages provide examples, not a complete independent ecosystem comparison. |
How to interpret Solana’s published figures
Solana’s Agent Registry page publishes figures of approximately 400 ms finality, transaction costs under $0.001, and capacity above 65,000 transactions per second. These are figures published by the Solana Foundation on its Agent Registry page. They are ecosystem claims, not an independently verified, like-for-like comparison with Ethereum or its layer-2 networks. Actual costs and behavior depend on transaction construction, network conditions, retries, congestion, and the infrastructure path you use.
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A synthetic transfer test is not enough. Build a small vertical slice that exercises the same contracts, payment protocol, wallet policy, RPC path, indexing, and retry logic as production.
- Record the workload: Measure requests per minute, peak bursts, transaction frequency, payload size, contract complexity, expected value per transaction, and how many operations can be batched.
- Define service-level targets: Set acceptable time to submit, observe, confirm, and settle. Separate user-visible latency from finality requirements.
- Test fee behavior: Capture fee variability, token conversion needs, failed-transaction costs, replacement or retry behavior, and the effect of congestion.
- Exercise failures: Simulate dropped RPC responses, duplicate submissions, stale block or slot data, indexer lag, rejected signatures, expired permissions, and partial service completion.
- Measure indexing and reconciliation: Verify how quickly your application can discover transactions, correlate them with requests, and recover when an event is missed.
- Test policy boundaries: Attempt an over-cap payment, a non-allowlisted recipient, an expired session key, a replayed request, and a contract method outside the agent’s role.
- Repeat under realistic load: Run the same scenario during normal and stressed conditions, documenting the network, RPC provider, client version, and configuration.
Compare the resulting cost, latency, failure rate, operational effort, and recovery time. The fastest nominal finality is not automatically the best choice if your indexer, wallet, or payment facilitator becomes the bottleneck.
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Language and contract skills
Choose a network your team can review and secure, not merely one with an attractive benchmark. Account for the languages your developers know, audited contract libraries, local testing, deployment tooling, upgrade procedures, and the ability to investigate a production incident.
Wallet and key management
Document how agent credentials are created, stored, rotated, scoped, and revoked. Decide whether the agent uses a dedicated account, a smart account, session keys, or another delegated mechanism. Separate signing authority from the model runtime where possible, and ensure the host cannot silently broaden policy.
RPC, indexing, and observability
Your application needs reliable transaction submission, confirmation tracking, historical queries, logs, metrics, alerting, and a fallback plan when an endpoint or indexer fails. Test the exact provider configuration rather than assuming that network-level availability translates into application-level reliability.
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Portability and dependency risk
Identify dependencies on a particular registry, facilitator, wallet, RPC endpoint, indexer, bridge, or token issuer. Record what can be replaced without rewriting contracts or migrating user state. If interoperability is a requirement, define the data and payment interfaces that must remain stable across networks.
A practical decision process
- Write the blockchain requirement in one sentence. For example: “The agent must pay independent data providers under a verifiable, capped policy.” If you cannot write a requirement like this, pause the chain selection.
- Separate private and shared state. Keep prompts, sensitive records, and model intermediates offchain unless another party must verify them.
- List trust claims. Decide whether you need identity, reputation, validation, auditability, or only payment settlement.
- Specify the payment flow. Choose per-request or metered behavior, token requirements, client support, facilitator responsibilities, refunds, and reconciliation.
- Write the authority policy. Include methods, recipients, assets, caps, expiry, revocation, escalation, monitoring, and recovery.
- Shortlist networks by fit. Check contracts, wallets, SDKs, registries, payment clients, RPC, indexing, and team skills.
- Run a workload-specific prototype. Measure latency, finality, fees, failures, retries, indexing, and operational effort using production-like flows.
- Choose an operating model. Document who controls keys, who responds to incidents, how upgrades are approved, and how the system behaves when the chain or a dependency is unavailable.
- Revalidate before launch. Network features, wallet support, payment clients, and infrastructure limits change. Confirm the exact versions and target network at implementation time.
Common mistakes and how to avoid them
Choosing by transaction-per-second claims
Capacity figures are not a substitute for an application test. Your agent may be limited by contract execution, account contention, RPC quotas, indexer lag, payment-client behavior, or the time needed to reconcile failures.
Equating a registry with trust
Identity and reputation records help applications make decisions, but they can be incomplete, manipulated, stale, or disconnected from the quality of a particular output. Define independent validation and dispute handling where the consequence of an error is significant.
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A model can be manipulated by hostile prompts, compromised tools, malformed external data, or bugs in the host. Use policy-bound delegation, limits, allowlists, expiry, monitoring, and a tested emergency stop instead of unrestricted signing authority.
Assuming HTTP 402 means the same payment flow everywhere
MPP and x402 differ in headers, data models, and supported payment patterns. Confirm the client and network combination you will deploy, including capped sessions, exact or upto schemes, token support, and settlement behavior.
Putting every operation onchain
Onchain state is valuable when others must verify or coordinate around it. It is usually a poor place for private prompts, large intermediate payloads, or high-frequency steps that do not need consensus. Keep those operations offchain and anchor only the necessary commitments or results.
Decision checklist
- Have you identified a requirement that truly needs shared state, programmable settlement, public auditability, or trust coordination?
- Which claims must be checked: identity, reputation, execution, inference, authorization, or payment?
- Is your payment pattern per-request or metered, and does the chosen client support it on the target network?
- Are stablecoins, wallets, facilitators, refunds, and reconciliation defined?
- Can the agent operate only within explicit methods, recipients, assets, caps, and expiry windows?
- Is there human approval for exceptional actions and a tested revocation path?
- Have you measured transaction frequency, latency, finality, fees, retries, failures, indexing, and RPC behavior with the real workload?
- Can your team secure contracts, keys, wallet policies, infrastructure, monitoring, and incident response?
- What happens if a registry, facilitator, RPC provider, indexer, wallet, or chain endpoint is unavailable?
- Have you documented which features are ecosystem claims and which results your own prototype verified?
Final recommendation
Select the chain that satisfies a clearly stated onchain requirement and that your team can secure and operate end to end. Ethereum may fit an application that needs its contract, smart-account, registry, or layer-2 ecosystem and can validate the exact payment path. Solana may fit an application whose measured workload benefits from its chosen transaction environment and whose MPP, x402, registry, wallet, and infrastructure stack are compatible. Neither choice should be made from a headline performance number or a protocol name alone.
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