API

Claude Opus 4.8 API Guide: Model ID, Pricing, Examples and Migration Tips

May 28, 2026 Updated May 28, 2026 9 min read

Independent, unofficial guide — not affiliated with Anthropic. Verify all facts against official sources.

TL;DR

Call Claude Opus 4.8 with model ID claude-opus-4-8. Migration is mostly swapping that string — but re-test prompts, outputs and cost. Output tokens are the expensive side, so judge cost by task success rate, not just unit price.

Everything a developer needs to start with Claude Opus 4.8: the model ID, pricing, a minimal request, a migration checklist and the mistakes that trip people up.

Verify this

Model IDs and pricing change. Treat the values here as a starting point and confirm against Anthropic's model & pricing docs before you ship.

Quick API facts

Model ID

claude-opus-4-8

Context window

1M tokens

Input price

$5 / 1M input tokens

Output price

$25 / 1M output tokens

Claude Opus 4.8 model ID

Set the model field to claude-opus-4-8. That single string is what routes your request to this version.

Fig. 1 — Request pathWhat happens on each call
Your app
Anthropic API/v1/messages
claude-opus-4-8model field
Response
The model ID is the only routing decision you make per request. Everything else is your prompt and parameters.

Pricing

Fig. 2 — Cost modelInput vs output, and the cost that matters
Input tokens$5 / 1M
Output tokens$25 / 1M

The cost that actually matters

effective cost ≈ tokens × unit price × retries ÷ success rate

Output is the expensive side, so a model that gets a long task right on the first try can be cheaper overall than a "cheaper" model you have to re-run three times.

Working figures: $5 / 1M input tokens, $25 / 1M output tokens. Verify on Anthropic's pricing page.

Our take

Don't price a model on its token rate alone. A model that finishes a long task correctly on the first attempt can be cheaper than a "cheaper" one you re-run three times. Measure cost per successful outcome.

Basic API usage example

The standard Messages API shape — Python first, then cURL:

quickstart.py
import anthropic

client = anthropic.Anthropic()  # reads ANTHROPIC_API_KEY from env

msg = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain what changed in this diff."},
    ],
)

print(msg.content[0].text)
request.sh
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, Opus"}]
  }'

Verify this

SDK names, versions and headers evolve. Confirm the current install command, the anthropic-version header and the response shape in the official quickstart before relying on this in production.

Migration checklist

Fig. 3 — MigrationFrom an older Opus to 4.8 in five steps
  1. 1

    Swap the model ID

    API
    Change claude-opus-4-7 claude-opus-4-8 in one place (centralize it if you haven't).
  2. 2

    Re-run your prompt suite

    Eval
    Run your saved prompts/evals and diff outputs against the old version — format, tone and structure can shift.
  3. 3

    Check tool-use & JSON outputs

    Agents
    If you use tools or structured outputs, verify schemas still validate and tool calls still fire as expected.
  4. 4

    Compare cost on a sample

    Cost
    Measure tokens and effective cost on a representative batch, including any change in retries.
  5. 5

    Roll out behind a flag

    Ship
    Ship to a fraction of traffic first; keep a one-line rollback to the previous model ID.
A model swap is one line; a safe migration is a short process. Don't skip the eval and cost steps.

Common mistakes

  • Hard-coding the model ID everywhere. Keep it in one constant so the next migration is trivial.
  • Skipping the eval pass. "It's the same family" still changes outputs — diff before you trust it.
  • Pricing on unit rate only. Ignoring retries and success rate hides the real cost.
  • Maxing effort on everything. Use effort control deliberately — high effort on trivial tasks just burns budget.

When to use Opus instead of cheaper models

Fig. 4 — Model choiceOpus or something cheaper?
How complex and high-stakes is the task?
Complex / long / agentic
Use Claude Opus 4.8 — reliability pays for itself.
Mixed
Route hard tasks to Opus, simple ones to a cheaper model.
Short / simple / high volume
A cheaper or faster model is usually the better value.
Reach for Opus when the cost of a wrong answer is high or the task is long and multi-step. Otherwise, save the budget.

Our take

Next: the version comparison for the upgrade verdict, the prompt kit for copy-ready prompts, or the model reference page for the quick facts.

Frequently asked questions

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