Developer Platform Updates & Release Notes

AI Gateway's REST API now returns consistent responses when an AI provider rejects credentials. The change applies to POST /ai/run ↗︎.

Scenario

Previous AI Gateway response

New AI Gateway response

ElevenLabs

Provider-specific UserCredentialsError with HTTP 403

HTTP 401 with error code 2009

Google Vertex

HTTP 500 for rejected credentials, with upstream retries

HTTP 401 with error code 2009; the request fails without retrying the provider

All other providers

HTTP 402 or another provider-specific status for rejected credentials

HTTP 401 with error code 2009

When using Unified Billing, the provider rejects the credentials

Provider-specific authentication error

HTTP 503

Update applications that handle AI Gateway REST API errors to treat HTTP 401 as an invalid or rejected provider credential.

For details about providing provider credentials, refer to Bring your own provider keys.

Web Search API is now available in beta. Web Search API lets your AI agents and applications search the Internet and ground their responses in live information, instead of guessing URLs or relying on a model's training cutoff.

At launch, you can choose between three search providers: Ceramic.ai, Exa, and Linkup. All three support Zero Data Retention for requests made through Cloudflare, and all have committed to Cloudflare's verified bot crawling standards.

Web Search API runs through AI Gateway, so search requests appear in your gateway logs and are billed to your AI Gateway credits at each provider's list API price, with no additional markup. You can also bring your own provider API key.

Call Web Search API with the REST API:

curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/websearch/ \
  --request POST \
  --header "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
    "query": "What are some fun things to do in Salt Lake City as fall approaches?",
    "provider": "ceramic",
    "limit": 5,
    "options": { "gateway": { "id": "default" } }
  }'

Or from a Worker with the AI binding:

const response = await env.AI.websearch({
	gatewayId: "default", …

The Agents SDK now provides first-class support for building agents using the Pi harness. You can build long-running agents using the combination of Pi 1.0 ↗︎, Pi Durable ↗︎, and the new PiHarness class that the Cloudflare Agents SDK provides, ensuring your agent's work is durably persisted, even if interrupted mid-turn.

Built with Earendil ↗︎, this integration is our first step toward first-class support for third-party agent harnesses on Cloudflare.

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Deploy to Cloudflare

Beta …

Jurisdictions for Workers KV namespaces are now generally available. When you create a namespace, you can set a jurisdiction to make sure the namespace's data is only durably stored within that region. Jurisdictions can help you comply with data localization regulations such as GDPR or FedRAMP. Supported jurisdictions are eu, us, and fedramp.

A jurisdiction can only be set when a namespace is created, using the Cloudflare dashboard, Wrangler, the cf CLI, or the REST API, and cannot be added or changed afterwards.

npx wrangler@latest kv namespace create <NAMESPACE_NAME> --jurisdiction=eu

cf kv namespaces create --title <NAMESPACE_NAME> --jurisdiction eu

curl "https://api.cloudflare.com/client/v4/accounts/$ACCOUNT_ID/storage/kv/namespaces" \
  --request POST \
  --header "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
    "title": "<NAMESPACE_NAME>",
    "jurisdiction": "eu"
  }'

Workers can still access a namespace restricted to a jurisdiction from anywhere in the world, and KV data can be cached outside the jurisdiction on Cloudflare's network. The jurisdiction only controls where the namespace's data is durably stored.

To learn more, refer to Data location.

Meet @cf/cloudflare/clef and @cf/cloudflare/clef-flash, the first models trained by the Cloudflare Workers AI team, available on Workers AI today.

Clef is a decision model, in the same family as Typesafe's Jev ↗︎. Instead of generating text, it reads an input state and a set of typed questions, then returns a probability for every allowed answer. Your agent gets a structured decision it can act on immediately, for example: route the ticket, block the request, or escalate to a human. There is no free-form output to parse and no reasoning tokens to wait for.

Both models are hosted on Workers AI as Clef and Clef-flash. We are also open-sourcing the weights under the Apache 2.0 license on Hugging Face: Clef ↗︎ and Clef-flash ↗︎. Read the launch blog post ↗︎ for the full story, including how we trained them. …

@cloudflare/workers-oauth-provider ↗︎ is now v1, with a new split API. One Worker acts as the authorization server: it signs users in and issues tokens. Your MCP server acts as the resource server, and can run in another Worker. It validates each token with the authorization server over a Service Binding, without crossing the public Internet.

• It supports the MCP 2026-07-28 authorization specification ↗︎, including Client ID Metadata Documents ↗︎ and issuer identification ↗︎. It still works with older clients, including those using Dynamic Client Registration ↗︎.
• insufficientScope() gives you step-up authorization ↗︎ in one line. …

AI Search is now generally available. Usage-based billing begins on November 1, 2026, with included monthly ingestion, storage, semantic query, and full-text query usage. Cloudflare will send a reminder email the week before billing begins.

Refer to Limits & pricing for rates and included usage.

Hybrid search is on by default

New AI Search instances use hybrid search by default. Hybrid search combines semantic vector retrieval with full-text matching. You can choose a different index method when you create an instance.

Refer to Hybrid search for details.

Workers AI embeddings and reranking are included

Workers AI embedding and reranking calls made by AI Search are included in AI Search pricing. These calls no longer appear on your Workers AI bill or in your AI Gateway logs. Generation, query rewriting, and external providers continue to use your account and gateway.

Refer to Limits & pricing for details.

Multimodal model and image support

…

Artifacts, Cloudflare's versioned file system that speaks Git, is now in open beta. Artifacts is built for scale, so you can create a repository per project, user, session, or task.

With Artifacts, you can:

• Deploy repositories to Workers — Connect an Artifacts repository through Workers Builds. Pushes to the production branch deploy the updated Worker, while other branches create or update Worker Previews.
• Programmatically manage repositories — Use an Artifacts binding from a Worker to create or fork repos, inspect files and commits, read files by path, and issue repo-scoped Git tokens.
• React to repository changes — Subscribe to events when a repository is created, imported, forked, deleted, pushed to, cloned, or fetched.
• Control where repository data is stored — Choose to store and process your data in the US or EU.
• Monitor repository usage — View total operations, pulls, pushes, errors, and error rates in the Cloudflare dashboard or via API for analytics.…

Basin, formerly the Cloudflare Data Platform, is now generally available. Basin brings an end-to-end analytics platform to the Developer Platform, enabling you to collect data from a variety of sources, such as apps, infrastructure, devices, and other Cloudflare services, then query it to answer analytical questions.

Basin Pipelines

Basin Pipelines, formerly Cloudflare Pipelines, ingests events from Workers, HTTP endpoints, and Cloudflare Logpush. It transforms events with SQL and ingests them into Iceberg tables or files on R2. With Basin Pipelines you can:

• Ingest application and device events through HTTP endpoints or Workers bindings.
• Filter and reshape Cloudflare logs before storing them as Iceberg tables, Parquet, or JSON.
• Catch schema mismatches with typed bindings and investigate dropped events in the dashboard.

Basin Catalog

Basin Catalog, formerly R2 Data Catalog, manages and automatically maintains Apache Iceberg tables ↗︎ to keep them fast, cost-efficient, and accessible to any compatible query engine. With Basin Catalog you can:

• Connect DuckDB, Spark, Snowflake, or PyIceberg to the same tables. …

Durable Objects remain active while handling a request from a connected client. This change applies when no client is connected, such as when an agent continues a submitted job after its client disconnects.

This behavior is the default for Workers with a compatibility date of 2026-10-01 or later. To use it with an earlier date, add the durable_object_io_tasks_prevent_eviction compatibility flag. To opt out, add the durable_object_io_tasks_do_not_prevent_eviction flag.

Pending service binding requests now keep Durable Objects running while they wait for a response. Pending calls to another Durable Object through remote procedure call (RPC) or fetch(), as well as this.ctx.container.monitor(), now also keep the Durable Object running.

Promises passed to this.ctx.waitUntil() and pending setTimeout() and setInterval() timers also receive this protection.

Previously, Cloudflare could shut down an idle Durable Object while one of these operations remained pending without a connected client. This could stop unfinished work. …

The Workers Web Crypto API now supports ML-KEM-768, ML-KEM-1024, ML-DSA-44, ML-DSA-65, and ML-DSA-87. ML-KEM establishes shared secrets, while ML-DSA signs and verifies data.

The opt-in API also adds key encapsulation and decapsulation methods, getPublicKey(), SubtleCrypto.supports(), and JSON Web Keys (JWKs) with the AKP key type.

Turn on the webcrypto_modern_algorithms compatibility flag to use these features:

{
  "$schema": "./node_modules/wrangler/config-schema.json",
  "compatibility_flags": [
    "webcrypto_modern_algorithms"
  ]
}

compatibility_flags = ["webcrypto_modern_algorithms"]

This example uses ML-KEM-768 to establish the same shared secret on both sides:

src/index.jsjs

const keyPair = await crypto.subtle.generateKey("ML-KEM-768", false, [
	"encapsulateBits",
	"decapsulateBits",
]);

if (!("publicKey" in keyPair)) {
	throw new Error("Expected an ML-KEM key pair");
}

const { sharedKey, ciphertext } = await crypto.subtle.encapsulateBits(
	"ML-KEM-768",
	keyPair.publicKey,
);

const recoveredSharedKey = await crypto.subtle.decapsulateBits(
	"ML-KEM-768",
	keyPair.privateKey,
	ciphertext,
);

src/index.tsts

const keyPair = await crypto.subtle.generateKey("ML-KEM-768", false, [
	"encapsulateBits",
	"decapsulateBits",
]);

if (!("publicKey" in keyPair)) {
	throw new Error("Expected an ML-KEM key pair");
}

const { sharedKey, ciphertext } = await crypto.subtle.encapsulateBits(
	"ML-KEM-768",
	keyPair.publicKey,
); …

Containers now support the durable_object scheduling policy in public beta. This policy lets a Durable Object select the image and instance size for a Container at runtime instead of using one centrally managed configuration for the application.

To use custom images, configure the policy and one or more named images in Wrangler:

{
	"containers": [
		{
			"class_name": "AgentComputer",
			"scheduling_policy": "durable_object",
			"images": {
				"base": {
					"dockerfile": "./container/Dockerfile",
				},
			},
		},
	],
}

[[containers]]
class_name = "AgentComputer"
scheduling_policy = "durable_object"

[containers.images.base]
dockerfile = "./container/Dockerfile"

Wrangler prepares each image and exposes its immutable reference through ctx.container.images. Supply that reference and an instance size when you start the Container:

src/index.jsjs

this.ctx.container.start({
	image: this.ctx.container.images.base,
	enableInternet: false,
	instance: "standard-2",
});

src/index.tsts

this.ctx.container.start({
	image: this.ctx.container.images.base,
	enableInternet: false,
	instance: "standard-2",
});
``` …

Containers now support snapshot APIs in public beta for saving and restoring point-in-time filesystem state. Create a snapshot first, then pass it back to start() to restore files after container sleep, restart, or handoff to another Durable Object.

Use snapshotContainer() through the Durable Object Container API to capture the full container filesystem. Create a snapshot from a running Container, store its handle, and pass that handle to start() when you restore it later:

src/index.jsjs

import { DurableObject } from "cloudflare:workers";

export class MyDurableObject extends DurableObject {
	async saveSnapshot() {
		// Create a snapshot from the running Container.
		const containerSnapshot = await this.ctx.container.snapshotContainer({});

		await this.ctx.storage.put("containerSnapshot", containerSnapshot);
	}

	async restoreSnapshot() {
		// Restore the saved snapshot later.
		const containerSnapshot = await this.ctx.storage.get("containerSnapshot");

		if (!containerSnapshot) {
			return;
		}

		this.ctx.container.start({ containerSnapshot, enableInternet: false });
	}
}

src/index.tsts

import { DurableObject } from "cloudflare:workers";

export class MyDurableObject extends DurableObject {
	async saveSnapshot() {
		// Create a snapshot from the running Container. …

Sandbox SDK 1.0 is available. Your own Durable Object class now controls each sandbox container directly, through the Durable Object container API on this.ctx.container.

With 1.0, your class can:

• Choose the image and instance size each time it starts a sandbox. One class can run sandboxes on different images, and a deploy does not restart sandboxes that are running.
• Save the files of a sandbox as a snapshot, in public beta, and start the same sandbox or a new one from it.
• Decide when each sandbox stops, for example when a task finishes, when its user goes idle, or after it saves a snapshot.
• Run commands with streamed input and output, send them signals, and open terminals.
• Serve previews from ports in the sandbox, with your own hostnames and authentication.
• Handle outbound requests for each hostname in Worker code, so credentials and bindings stay in your Worker.
• Expose only the methods that you want callers to use. …

AI Gateway now supports Machine Payments in beta. With Machine Payments, clients can use the x402 protocol to pay for eligible inference requests directly from a stablecoin wallet instead of maintaining a prepaid credit balance.

Machine Payments is available for the /ai/run endpoint with select open models. To request x402 payment, authenticate with a Cloudflare API token and include the Cloudflare-specific Payment-Method: x402 header:

curl -iX POST "https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run" \
  --header "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \
  --header "Payment-Method: x402" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "z-ai/glm-4.7-flash",
    "input": {
      "messages": [
        {
          "role": "user",
          "content": "What is Cloudflare?"
        }
      ]
    }
  }'

An x402-compatible client handles the payment challenge, signs an authorization from the client's wallet, and retries the request. Machine Payments currently requires customers to be based in the United States and have a credit card on file.

For prerequisites, eligible models, and transaction details, refer to Machine Payments (x402).

The WebSocket adapter for Cloudflare's Realtime SFU is now generally available. The SFU (selective forwarding unit) is managed WebRTC infrastructure for live audio, video, and data across Cloudflare's global network in 330+ cities ↗︎.

The adapter connects live calls to any server that accepts WebSockets, such as a Durable Object. It delivers uncompressed pulse-code modulation (PCM) audio and JPEG video frames. Your backend can process this media without implementing a WebRTC client.

What you can build

• Transcribe or record call audio, or let a voice agent hear and respond to participants. The AI audio example uses Durable Objects and Workers AI for transcription and speech generation. Separate adapters receive PCM audio and send generated speech back to participants.
• Analyze images or build previews from live video. The WebRTC-to-JPEG example ↗︎ sends a browser's camera stream to a Durable Object as JPEG frames at one frame per second by default.

What changes for existing integrations

…

AI Gateway User Insights now gives you more context about the traffic flowing through your gateway. It shows what users and agents are doing with AI, and where a selected model may be more capable than a task requires.

On the analysis side, User Insights groups conversations by task, tracks conversation turns, and helps you compare model fit with cost and latency.

User Insights task and model analysis grouped by task categories

The Potential Savings view highlights requests that may work with faster or less expensive models without compromising output quality. These are the same signals that Cloudflare's Auto Router uses to select a model based on task and cost.

Potential Savings view comparing tasks and suggested models

These new insights are available to all AI Gateway customers at no additional cost. For more information, refer to User Insights.

Browser Run sessions now accept multiple concurrent connections. Before, a session accepted only one connection at a time, and other Workers had to wait until that connection closed. Now multiple Workers can connect to the same browser at the same time.

Each puppeteer.connect() call opens its own Chrome DevTools Protocol (CDP) connection. Create a separate browser context for each request to keep its pages, cookies, and storage apart from other clients.

const browser = await puppeteer.connect(env.MYBROWSER, sessionId);
const context = await browser.createBrowserContext();

try {
	const page = await context.newPage();
	await page.goto("https://example.com");
	// ...
} finally {
	await context.close();
	await browser.disconnect(); // keep the shared browser running
}

const browser = await puppeteer.connect(env.MYBROWSER, sessionId);
const context = await browser.createBrowserContext();

try {
	const page = await context.newPage();
	await page.goto("https://example.com");
	// ...
} finally {
	await context.close();
	await browser.disconnect(); // keep the shared browser running
}

Sharing sessions means fewer new browsers to launch, less cold-start time, and fewer concurrent browsers counted against your limits.

Concurrent connections require @cloudflare/puppeteer version 1.1.0 or later. …