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How to Fix Databricks Claude PERMISSION_DENIED Rate Limit of 0 (TRIAL_VERIFIED Trust Tier): Step-by-Step Guide

How to Fix Databricks Claude PERMISSION_DENIED Rate Limit of 0 (TRIAL_VERIFIED Trust Tier): Step-by-Step Guide

Every Claude and GPT-5.x request returns PERMISSION_DENIED with a rate limit of 0. The endpoint settings look fine. Llama and other open models work. This is a workspace-level trust tier issue — here is how to confirm it, what it means, and how to escalate for an upgrade to PAYABLE_VERIFIED.

0
The Databricks-set rate limit blocking every Claude and GPT-5.x request — cannot be changed from the workspace UI
TRIAL_
VERIFIED
The workspace trust tier suspected when premium hosted models are blocked regardless of billing status
Llama
works
Open-source models (Llama, DBRX) are not subject to this Databricks-set platform restriction
Sales/
Support
The only path to resolution — workspace trust tier changes require Databricks backend team action
⚠ The Error You Are Seeing

Every request to databricks-claude-opus-4-8 (and other premium hosted models including GPT-5.x variants) fails immediately with:

// InternalError — every Claude/GPT-5.x request from the AI Playground or API
{
  "error_code": "PERMISSION_DENIED",
  "message": "PERMISSION_DENIED: The endpoint is temporarily disabled
                due to a Databricks-set rate limit of 0."
}

// What you have already verified:
// ✓ Billing is active — workspace is on Premium pricing tier
// ✓ system.ai schema is empty/unconfigured — no Unity Catalog restrictions
// ✓ Cross-geo data processing is enabled — not a regional issue
// ✓ Reproduced in West Europe AND France Central — not region-specific
// ✓ Llama, DBRX, and other open models work fine
// ✗ Only Claude and GPT-5.x (premium hosted models) return rate limit of 0
Root Cause

Why This Is Happening — The TRIAL_VERIFIED Trust Tier

This error is not a misconfiguration and it cannot be fixed from within the workspace. The "Databricks-set rate limit of 0" is applied at the platform level by Databricks — not at the endpoint level by the workspace administrator. It reflects a workspace trust tier classification that restricts access to premium hosted models (Claude, GPT-5.x) regardless of what the endpoint settings, AI Gateway configuration, or billing status shows in the workspace UI.

Databricks maintains an internal workspace trust tier system. Workspaces that signed up through certain channels, or that Databricks has classified as trial or evaluation accounts, are placed in a TRIAL_VERIFIED trust tier. At this tier, Databricks applies a platform-enforced rate limit of 0 to premium hosted models — meaning no requests are allowed regardless of what QPM/TPM limits are configured in the AI Gateway or Serving endpoint settings. This is Databricks's fraud and abuse prevention mechanism for high-value model endpoints.

The reason Llama and other open-source models still work is that they are not subject to this Databricks-set platform restriction — the premium model gate specifically targets pay-per-token endpoints that route to external model providers (Anthropic for Claude, OpenAI for GPT-5.x). Databricks bears the cost of these API calls and therefore gates access at the workspace trust tier level before the billing relationship is confirmed.

The fix requires Databricks to upgrade the workspace trust tier from TRIAL_VERIFIED to PAYABLE_VERIFIED. This is a backend operation — it cannot be performed from the workspace console, the Databricks portal, or any self-service mechanism. It requires contact with Databricks Sales or Databricks Support.

Figure 1 — How the platform-level rate limit of 0 blocks premium models regardless of workspace configuration
Your Code /AI PlaygroundAPI requestFoundation ModelAPI Endpointdatabricks-claude-opus-4-8AI GatewayUser rate limits: ✓Endpoint limits: ✓QPM/TPM config: ✓These don't matter herePLATFORM RATE LIMITTRUST TIER CHECKTRIAL_VERIFIED tierRate limit = 0 → BLOCKEDCannot be changed from UIPERMISSION_DENIED: rate limit of 0WHY OPEN-SOURCE MODELS (LLAMA, DBRX) STILL WORKYour RequestLlama endpointPlatform check — no restriction✓ WorksOpen-source models are Databricks-hosted at their own cost — no external API billing → no trust tier gate
The platform trust tier check runs before any workspace-level AI Gateway or endpoint rate limit configuration — no workspace setting can override it
Step 1 — Confirm the Diagnosis

Confirming It Is a Trust Tier Issue — Not a Configuration Problem

Before contacting Databricks, confirm this is definitely the trust tier issue and not a different configuration problem. Work through this checklist — if all items pass and you still get the rate limit of 0 error, the trust tier is the confirmed cause.

1
Databricks Workspace → Serving → Foundation Models → Try a Llama model

Confirm open-source models work while premium models fail

In the AI Playground, switch from databricks-claude-opus-4-8 to databricks-meta-llama-3-3-70b-instruct and send a test message. If Llama responds successfully but Claude returns PERMISSION_DENIED, this confirms the block is model-specific and applied at the platform level — not a workspace network issue, not an authentication problem, and not an AI Gateway misconfiguration. Log this result for your support ticket.

2
Account Console → Serving → [claude endpoint] → Rate limits

Verify endpoint-level rate limits are not set to 0 from within the workspace

Navigate to Serving → Foundation Model endpoints. Open the databricks-claude-opus-4-8 endpoint. Check the AI Gateway tab — verify that no rate limit in the workspace configuration is set to 0. If the workspace UI shows "No limit" or a positive value but the error still says "rate limit of 0", this confirms the block is coming from the Databricks platform layer — not the workspace configuration.

Note the distinction: a workspace admin setting a rate limit to 0 in the UI produces the error message "The endpoint is disabled due to a rate limit set to 0". The trust tier error reads "The endpoint is temporarily disabled due to a Databricks-set rate limit of 0" — the word Databricks-set is the key indicator that the block comes from Databricks's platform, not your configuration.

3
Databricks REST API test from outside the Playground

Reproduce via direct API call to rule out Playground-specific issues

Make a direct REST API call to the Foundation Model endpoint. If this also returns PERMISSION_DENIED with rate limit of 0, the Playground is not involved and the block is at the platform level.

cURL — Direct API test to confirm PERMISSION_DENIED is not Playground-specific# Replace YOUR_WORKSPACE_URL and YOUR_PAT_TOKEN with your values curl -X POST \
  "https://YOUR_WORKSPACE_URL/serving-endpoints/databricks-claude-opus-4-8/invocations" \
  -H "Authorization: Bearer YOUR_PAT_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"messages": [{"role": "user", "content": "Hello"}], "max_tokens": 50}'

# Expected response confirming TRUST TIER block (not a Playground issue):
# {"error_code":"PERMISSION_DENIED","message":"PERMISSION_DENIED: The endpoint is
# temporarily disabled due to a Databricks-set rate limit of 0."}

# Also test an open-source model to confirm those work: curl -X POST \
  "https://YOUR_WORKSPACE_URL/serving-endpoints/databricks-meta-llama-3-3-70b-instruct/invocations" \
  -H "Authorization: Bearer YOUR_PAT_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"messages": [{"role": "user", "content": "Hello"}], "max_tokens": 50}'
# Expected: successful response — confirms block is model-specific (trust tier gate)
4
Settings → Account Console → General → Workspace details

Record workspace details for the support ticket

Gather the following information — you will need all of it for the Databricks support ticket or Sales conversation:

  • Workspace ID — visible in the URL when logged into the workspace (e.g. https://adb-XXXXXXXXXX.X.azuredatabricks.net)
  • Account ID — from Account Console → top right or Settings
  • Cloud platform — Azure / AWS / GCP
  • Region(s) tested — e.g. West Europe, France Central
  • Pricing tier — Premium / Enterprise
  • Exact error message — screenshot and the JSON response
  • Models affected — list all premium models blocked
  • Models working — Llama, DBRX, others that succeed
Figure 2 — TRIAL_VERIFIED vs PAYABLE_VERIFIED: what each tier allows for Foundation Model APIs
CAPABILITYTRIAL_VERIFIEDPAYABLE_VERIFIEDOpen-source models (Llama, DBRX, Mistral)✓ Available✓ AvailableAnthropic Claude (all variants)✗ Rate limit = 0✓ Full accessOpenAI GPT-5.x hosted models✗ Rate limit = 0✓ Full accessAI Gateway endpoint rate limits (workspace-set)⚠ Overridden by platform✓ RespectedPay-per-token billing for premium models✗ Not billed (blocked)✓ Billed per tokenPAYABLE_VERIFIED is not a product tier — it is an internal trust classification changed by Databricks backend teams upon request
PAYABLE_VERIFIED is confirmed by Databricks verifying active billing commitment — being on the Premium pricing tier in the portal is not sufficient by itself
FactorTRIAL_VERIFIED (current)PAYABLE_VERIFIED (needed)
Claude models✗ Databricks-set rate limit of 0✓ Normal QPM/TPM limits apply
GPT-5.x models✗ Databricks-set rate limit of 0✓ Normal QPM/TPM limits apply
Llama / DBRX / open models✓ Works normally✓ Works normally
AI Gateway configuration⚠ Visible but overridden for premium models✓ Fully respected for all models
Error message indicator"Databricks-set rate limit of 0"No platform block error
How to changeCannot self-serve — backend onlyDatabricks Sales or Support request
Typical triggerTrial signup, evaluation workspace, certain partner channelsConfirmed active billing commitment
The Fix — Contact Databricks
Step 2 — Request Trust Tier Upgrade

How to Request Upgrade to PAYABLE_VERIFIED — Two Paths

There is no self-service mechanism to change the workspace trust tier. It must be changed by the Databricks backend team in response to a support ticket or a Sales engagement. Use whichever path is available to you first — both escalate to the same team.

A
help.databricks.com → Create Support Ticket → Technical Issue

Path A: Open a Support Ticket (if you have a support plan)

Log into help.databricks.com. Select Create a support case. Set the severity to Severity 1 / P1 if the issue is blocking production workloads (all Claude/GPT-5.x models unavailable). Use the support ticket template below — copy it exactly and fill in your workspace details. Route to: Model Serving / Foundation Model APIs team.

B
Contact your Databricks Account Executive or Customer Success Manager

Path B: Escalate via your Databricks Sales / Account team

If you have an assigned Databricks Account Executive or Customer Success Manager, contact them directly. This is often the fastest path — AEs can initiate the trust tier upgrade internally without the support ticket process. Reference the error and the workspace ID, and ask them to escalate to the Model Serving / Foundation Model APIs team to upgrade the workspace to PAYABLE_VERIFIED trust tier.

📋 Support Ticket Template — Copy and Fill In

Subject: URGENT: Premium hosted models (Claude, GPT-5.x) blocked by Databricks-set rate limit of 0 — suspected TRIAL_VERIFIED workspace trust tier

Severity: P1 — All Claude and GPT-5.x Foundation Model API endpoints unavailable

Route to: Model Serving / Foundation Model APIs team

Support Ticket Body — Copy, fill in bracketed fields, and submit## Summary
All premium hosted Foundation Model API endpoints (Anthropic Claude variants, OpenAI
GPT-5.x) are returning PERMISSION_DENIED with a Databricks-set rate limit of 0.
Open-source models (Llama, DBRX) work correctly. This is blocking all AI development
and evaluation work on this workspace.

## Error Received
{"error_code":"PERMISSION_DENIED","message":"PERMISSION_DENIED: The endpoint is
temporarily disabled due to a Databricks-set rate limit of 0."}

## Workspace Details
- Workspace URL: [https://adb-XXXXXXXXXX.X.azuredatabricks.net]
- Workspace ID: [XXXXXXXXXX]
- Account ID: [your-account-id]
- Cloud: [Azure / AWS / GCP]
- Region(s): [West Europe, France Central — reproduced in both]
- Pricing Tier: [Premium / Enterprise]
- Billing: Active — [describe your subscription/billing arrangement]

## Troubleshooting Already Performed
- ✓ Account admin access confirmed
- ✓ Cross-geo data processing enabled (not a regional geo issue)
- ✓ system.ai schema empty — no Unity Catalog model restrictions
- ✓ Reproduced via direct REST API (not Playground-specific)
- ✓ Reproduced in multiple regions — not region-specific
- ✓ Workspace AI Gateway rate limits are NOT set to 0
- ✓ Llama/DBRX models work — only Claude and GPT-5.x are blocked

## Root Cause Suspected
This workspace appears to be in the TRIAL_VERIFIED trust tier, which applies a
Databricks-set rate limit of 0 to premium hosted models regardless of workspace-level
endpoint or AI Gateway configuration. This cannot be resolved from the workspace UI.

## Requested Action
Please verify the workspace trust tier and upgrade it to PAYABLE_VERIFIED to enable
access to premium hosted models including Anthropic Claude and OpenAI GPT-5.x via
the Foundation Model APIs. The workspace is on the Premium pricing tier with active
billing. This is not a serverless compute quota issue — please route to the
Model Serving / Foundation Model APIs team.

## Impact
Unable to use Claude models for development/evaluation in the AI Playground and via
Model Serving endpoints. This blocks all AI development work requiring premium models.
Interim Workaround
Interim Workaround — While Waiting for Resolution

What You Can Do While Waiting for the Trust Tier Upgrade

The trust tier upgrade is handled by Databricks's backend team and typically takes 1–3 business days once the ticket reaches the right team. In the meantime, there are two approaches to continue development work.

Option A — Use an External Model endpoint (Claude via Anthropic API directly)

Databricks supports External Models in Model Serving — you can configure an endpoint that proxies to the Anthropic API using your own Anthropic API key. This bypasses the Databricks-hosted Foundation Model API entirely and is not subject to the trust tier restriction. The endpoint is managed within Databricks for governance but calls Anthropic directly.

Python — Create an External Model endpoint for Claude using your Anthropic API key# Requires: pip install databricks-sdk from databricks.sdk import WorkspaceClient
from databricks.sdk.service.serving import (
  ExternalModel, ExternalModelProvider, ServingEndpointInput,
  ServedModelInput, AnthropicConfig
)

client = WorkspaceClient()

# Create an External Model endpoint pointing to Anthropic directly client.serving_endpoints.create(
  name="claude-external-anthropic",
  config=ServingEndpointInput(
    served_models=[
      ServedModelInput(
        name="claude-opus-4",
        external_model=ExternalModel(
          provider=ExternalModelProvider.ANTHROPIC,
          name="claude-opus-4-5", # Anthropic model name
          task="llm/v1/chat",
          anthropic_config=AnthropicConfig(
            anthropic_api_key="{{secrets/your-scope/anthropic-api-key}}"
          )
        )
      )
    ]
  )
)
print("External Claude endpoint created — bypasses trust tier restriction")

Option B — Use open-source models as a functional substitute

For evaluation and development tasks that can tolerate a different model, databricks-meta-llama-3-3-70b-instruct is not subject to the trust tier gate and provides strong performance for most development and prototyping use cases. This does not resolve the root cause but keeps development work moving while the trust tier upgrade is processed.

Figure 3 — Complete resolution flowchart: from error to confirmed fix
PERMISSION_DENIED: rate limit of 0Do Llama models work in same workspace?NODifferent issueCheck auth, network, workspaceregional availabilityYESConfirmed trust tierTRIAL_VERIFIED blockingpremium models onlyDoes workspace AI Gateway show rate limit = 0?YESAdmin set the limitRemove the 0 rate limitfrom AI Gateway configNOPlatform-level block confirmed: TRIAL_VERIFIED tierTwo parallel actions (do both simultaneously)Open P1 Support TicketRequest PAYABLE_VERIFIED tier1–3 business daysInterim: External ModelClaude via Anthropic API keyWorks immediately
Open the support ticket AND configure an External Model endpoint simultaneously — the support ticket fixes the root cause, the External Model keeps work moving
After the Upgrade

What to Expect After the Trust Tier Is Upgraded

Once Databricks upgrades the workspace to PAYABLE_VERIFIED, no additional configuration changes are needed. The platform-level rate limit of 0 is removed from the backend. The existing databricks-claude-opus-4-8 and other premium hosted model endpoints become immediately accessible — the same endpoint you have been trying to use will begin returning successful responses without any changes to the workspace settings, AI Gateway configuration, or endpoint definitions.

Verify by sending a test query from the AI Playground. The model selector should now show Claude responding normally. If the trust tier was upgraded but Claude still returns PERMISSION_DENIED, check whether the workspace endpoint-level AI Gateway rate limits were accidentally set to 0 at some point during troubleshooting — and reset them to a positive value or "No limit".

Python — Verify Claude is accessible after trust tier upgrade# Quick smoke test — run this after Databricks confirms the tier upgrade import os
from openai import OpenAI

client = OpenAI(
  api_key=os.environ.get("DATABRICKS_TOKEN"),
  base_url=f"{os.environ.get('DATABRICKS_HOST')}/serving-endpoints"
)

response = client.chat.completions.create(
  model="databricks-claude-opus-4-8",
  messages=[{"role": "user", "content": "Hello — confirm Claude is accessible."}],
  max_tokens=100
)

print(response.choices[0].message.content)
# Expected: a normal Claude response — trust tier upgrade confirmed working
# If still PERMISSION_DENIED: check AI Gateway rate limits in the workspace UI

Key Takeaways

✓The error "Databricks-set rate limit of 0" is distinct from "rate limit set to 0" — the word "Databricks-set" confirms the block originates at the platform level, not from workspace configuration.
✓This is not a misconfiguration. The TRIAL_VERIFIED trust tier applies a platform-enforced rate limit of 0 to premium hosted models regardless of what is set in the AI Gateway or endpoint settings.
✓Confirm the diagnosis: if Llama works but Claude/GPT-5.x fail with rate limit of 0, and the workspace AI Gateway shows no 0-limits, the trust tier is the confirmed cause.
✓The only fix is a Databricks backend operation — open a P1 support ticket or contact your Databricks Account Executive requesting upgrade to PAYABLE_VERIFIED trust tier for the affected workspace.
✓While waiting for the upgrade, configure an External Model endpoint using your own Anthropic API key — this bypasses the trust tier gate entirely and gives immediate access to Claude.
✓After the trust tier is upgraded, no configuration changes are needed — the existing premium model endpoints work immediately without any workspace changes.
✓Being on the Databricks Premium pricing tier with active billing is not sufficient by itself to get PAYABLE_VERIFIED status — it must be explicitly set by the Databricks backend team after verification.
Frequently Asked Questions
We are on the Databricks Premium tier with active billing — why are we still TRIAL_VERIFIED?
The pricing tier (Standard, Premium, Enterprise) is a separate classification from the workspace trust tier (TRIAL_VERIFIED, PAYABLE_VERIFIED). A workspace can be on the Premium pricing tier and still have TRIAL_VERIFIED trust tier status if the workspace was originally provisioned through a trial channel, an evaluation programme, or certain partner signup flows that do not automatically trigger the PAYABLE_VERIFIED upgrade. The billing relationship and the trust tier classification are maintained in separate systems, and transitioning billing to Premium does not automatically update the trust tier. A manual backend action by Databricks is required to sync the two.
Can I fix this by deleting and recreating the workspace?
No. The trust tier classification is tied to the account and workspace provisioning method, not to any workspace-level configuration. Creating a new workspace through the same account and channel is likely to result in the same TRIAL_VERIFIED classification. The correct path is to have Databricks upgrade the existing workspace's trust tier — not to recreate it.
Why does the error say "temporarily disabled" — will it resolve on its own?
The word "temporarily" in the error message is misleading in this context. The platform-level rate limit of 0 applied by the TRIAL_VERIFIED trust tier does not automatically resolve or time out — it persists until Databricks manually upgrades the workspace trust tier. The "temporarily" language is generic error message text that applies to other rate limit scenarios (such as transient platform issues) but in this case reflects a persistent configuration. It will not resolve without the trust tier upgrade.
How long does it take for Databricks to upgrade the trust tier after a support ticket?
Typically 1–3 business days once the ticket reaches the Model Serving / Foundation Model APIs team. The routing and prioritisation of the ticket is important — a P1 severity ticket routed to the correct team typically gets a faster response than a P3 ticket routed to general support. Using the template above and explicitly stating "TRIAL_VERIFIED to PAYABLE_VERIFIED upgrade request" in the subject helps ensure correct routing. If you have an assigned Databricks Account Executive, escalating through them is usually faster than the support ticket process.
Will the External Model workaround (using our own Anthropic API key) incur double billing?
When using an External Model endpoint in Databricks with your own Anthropic API key, you are billed directly by Anthropic for the token usage — Databricks does not charge for the model inference itself in this configuration. Databricks may charge for the compute time used by the serving endpoint. Once the trust tier is upgraded and you switch back to the Databricks-hosted Foundation Model API (databricks-claude-opus-4-8), billing reverts to Databricks's pay-per-token pricing. You are not double-billed at any point — the two endpoint types use different billing paths.
After the trust tier is upgraded, will we need to reconfigure anything?
No. The existing Foundation Model API endpoints (databricks-claude-opus-4-8 and others) are pre-configured and continue to exist unchanged. Once the platform-level rate limit of 0 is removed, requests to those endpoints succeed immediately without any workspace, endpoint, or AI Gateway changes. Run the Python smoke test above to confirm and then use the endpoints normally.

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