claude-opus-4-1 Deprecation | Migration Guide and temperature 400 Error Fix

Why claude-opus-4-1 Is Being Deprecated Now — Anthropic's Model Management Policy

On June 5, 2026, Anthropic updated its official documentation (Model Deprecations) to formally announce the deprecation of claude-opus-4-1-20250805. The deprecation date is August 5, 2026, 60 days after the notice.

Under Anthropic's model lifecycle policy, deprecations must be announced at least 60 days in advance to minimize impact on production applications. However, if you are calling claude-opus-4-1 across multiple services, identifying all call sites and completing the fixes and tests alone can take considerable effort. Sixty days goes by quickly.

After deprecation, calling claude-opus-4-1-20250805 will result in an error and halt processing. To avoid risking user-facing outages, it is essential to complete your migration before the deprecation date.

Why Anthropic Deprecates Models

Model deprecation is not a reduction in capability — it is a measure to encourage migration to newer, higher-performing models. claude-opus-4-8 offers improved reasoning accuracy and processing speed compared to claude-opus-4-1, delivering better results for the same use cases. The approach of reducing infrastructure maintenance costs for older models while encouraging users to migrate to the latest model is a common strategy also used by Google Gemini and the OpenAI GPT series.

This is not the first deprecation notice. Anthropic has previously deprecated models such as claude-2.0, claude-2.1, and claude-instant-1.2 under the same policy. Teams that did not act on the notice found their services stop working on the deprecation date. Acting early is the only defense.

Practical Impact of Removing temperature / top_p / top_k — Code Review to Avoid 400 Errors

The aspect most commonly overlooked during this migration is the specification change to sampling parameters. Starting with claude-opus-4-7, passing non-default values for temperature, top_p, or top_k will return an HTTP 400 error (source: Anthropic Model Deprecations / Messages API Reference).

This means simply swapping the model ID to claude-opus-4-8 is not enough. Code like the following will cause immediate errors after migration:

response = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    temperature=0,     # ← This will trigger a 400 error
    top_p=0.95,        # ← Same here
    messages=[...]
)

Steps to Scan Your Entire Codebase

To identify all occurrences of temperature, top_p, and top_k in your codebase, the following approach is reliable:

1. Run grep from the project root to list all files where the parameters appear
2. In each file, check whether non-default values are being passed to the parameters
3. For any occurrences found, either remove the parameter entirely or guard with conditional logic

grep -rn "temperature\|top_p\|top_k" ./src

Address each occurrence found using one of the following strategies:

1. Delete the parameter line: With new models, the default values provide optimal behavior, so explicitly passing them is often unnecessary
2. Guard with a model branch condition: During a transition period where old and new models run in parallel, check the model ID to decide whether to pass the parameters

params = {
    "model": model_id,
    "max_tokens": 1024,
    "messages": messages,
}
# temperature is prohibited for claude-opus-4-7 and later. opus-4-1 and opus-4-6 are both old-generation models with the same constraint, so they are grouped together in the condition
if "opus-4-1" in model_id or "opus-4-6" in model_id:
    params["temperature"] = 0

response = client.messages.create(**params)

How to Get Deterministic Output After the Default Is Removed

temperature=0 has been used to ensure "the same input always returns the same output." Since this is being removed in new models, use cases that require deterministic output need alternative approaches.

Recommended alternatives include:

1. Use structured output: Specifying a JSON schema via the tool use feature allows you to fix the structure of the output
2. Constrain variation through prompting: Include strong constraints in your prompt, such as "Always respond in the following format and include no other text"
3. Validate output and retry: Implement a mechanism that sends another request if the response does not match the expected format

Migration Steps to claude-opus-4-8 — Code Samples for Python / TypeScript / REST API

Swapping the model ID is fundamentally a one-line change. The following shows what needs to change in each SDK.

Changes in the Python SDK

If you are using the official Python SDK (anthropic-sdk-python v0.107.1), the only changes needed are updating the model= value and removing unnecessary parameters:

import anthropic

client = anthropic.Anthropic()

response = client.messages.create(
    model="claude-opus-4-8",    # ← Change this
    max_tokens=1024,
    # Remove temperature
    messages=[
        {"role": "user", "content": "Hello"}
    ]
)
print(response.content[0].text)

Check your SDK version with pip show anthropic and confirm it is v0.107.1 or later. The bug fix described later is included in this version.

Changes in the TypeScript / Node.js SDK

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

const response = await client.messages.create({
  model: "claude-opus-4-8",   // ← Change this
  max_tokens: 1024,
  // temperature: 0,          // ← Delete this line
  messages: [
    { role: "user", content: "Hello" }
  ],
});

console.log(response.content[0].text);

You can check the TypeScript SDK version with npm list @anthropic-ai/sdk. The latest release information is available on the anthropic-sdk-typescript releases page.

Changes for the REST API (cURL)

If you are calling the REST API directly, simply replace the model field in the request body and remove the temperature, top_p, and top_k fields:

curl https://api.anthropic.com/v1/messages \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello"}
    ]
  }'

Old vs. New Model ID Reference

Anthropic's official documentation (Model Deprecations) lists both the alias form (claude-opus-4-1) and the dated form (claude-opus-4-1-20250805) as deprecated. Whichever you are using, migration to claude-opus-4-8 is required.

Additional Checks for Foundry / Bedrock Users — Relationship with the SDK v0.107.1 Bug Fix

Users accessing claude-opus-4-1 through Amazon Bedrock or Foundry have additional items to verify during migration.

Migration Points for Amazon Bedrock

When using the API through Bedrock, model IDs follow Bedrock's own naming conventions. The most reliable way to confirm the exact model ID is through the AWS console or the following command:

aws bedrock list-foundation-models \
  --by-provider anthropic \
  --query "modelSummaries[*].[modelId,modelName]" \
  --output table

If you are calling through the Bedrock SDK (boto3), you also need to remove any occurrences of temperature, top_p, and topK in your inferenceConfig. It has been confirmed that even through Bedrock, these parameters return 400 errors with the new generation of models.

What Was Fixed in SDK v0.107.1

Python SDK v0.107.1 includes fixes for bugs that affected communication with claude-opus-4 series models. An issue where errors occurred under certain conditions during streaming response parsing has been resolved.

Upgrading the SDK to the latest version before migrating will prevent unexpected errors after changing the model ID. Use the following commands to upgrade:

# Python
pip install --upgrade anthropic

# Node.js
npm install @anthropic-ai/sdk@latest

SDK upgrades are backward-compatible in most cases, but it is still a good idea to run your existing tests after upgrading to confirm everything works correctly.

Tests to Run Before Migration and Common Pitfalls — Pre-Production Deployment Checklist

Before changing the model ID and deploying, it is strongly recommended to work through the following checklist in order.

Migration Checklist

1. Search your entire codebase for claude-opus-4-1 and identify all call sites
2. Search your entire codebase for temperature, top_p, and top_k and address each occurrence by removing or adding conditional guards
3. In a staging environment, change the model ID to claude-opus-4-8, run all API calls, and confirm no 400 errors occur
4. Sample the response content and quality to verify it is within acceptable range
5. Upgrade the SDK to v0.107.1 or later and re-run your tests
6. After the production deployment, monitor error rates for the first hour and be prepared to temporarily roll back to the old model ID if anything goes wrong

Common Pitfall: Mixing Aliases and Dated IDs

It is common for the same codebase to contain both claude-opus-4-1 (alias) and claude-opus-4-1-20250805 (dated form). Since both are subject to deprecation, use the following command to search for and replace both at once:

grep -rn "claude-opus-4-1" ./src

This grep will match both patterns.

Common Pitfall: Hardcoding in Configuration Files

Model IDs are often hardcoded not in source code but in configuration files or environment variable definitions. Make sure to include configuration files in your search, not just your code:

grep -rn "claude-opus-4-1" . \
  --include="*.json" \
  --include="*.yaml" \
  --include="*.yml" \
  --include="*.toml"

Common Pitfall: Custom Model ID Mappings for Foundry

Some Foundry users maintain their own internal model ID mappings for management purposes. In that case, do not forget to update the mapping in the Foundry management console as well. Changing the model ID on the code side alone may leave Foundry still pointing to the old model.

Monitoring Points After Production Migration

After migration, monitor the following metrics:

1. API error rate: An increase in 400 or 500 errors requires immediate action
2. Response latency: claude-opus-4-8 may have different latency characteristics compared to claude-opus-4-1
3. Output quality sampling check: Have a human review samples for the first week after migration

There is approximately two months until the deprecation date of August 5, 2026, but starting early is important to ensure adequate validation time in staging. Depending on the size of your codebase and the number of services involved, migration can take a month or more. Starting your codebase scan now is the best way to prevent a production incident.

Sources

• Anthropic Model Deprecations — Official list of deprecated models and deprecation dates (updated 2026-06-05)
• anthropic-sdk-python v0.107.1 Release Notes — Python SDK bug fix details
• anthropic-sdk-typescript Releases — Latest version information for the TypeScript SDK