Claude · Flagship · 200K context window

Claude Opus 4.8 pricing for data extraction

$0.0450 per call at 4,000 input / 1,000 output tokens.

Per call

$0.0450

10K calls/mo

$450

Cache savings

90% off input

Batch savings

50% off all

Calculate your Claude Opus 4.8 costs

Adjust token counts, volume, and discount toggles to model your data extraction spend. Prices verified daily against provider pricing pages.

Configure your usage

4,000
100100K
1,000
5050K
10,000
1001M

Estimated cost

Monthly cost
$450
10,000 calls/month
Cost per call$0.045
Daily cost$15
Input rate$5.00/MTok
Output rate$25.00/MTok
Analyze your real spend

Quick start

Call Claude Opus 4.8 with the Anthropic Python SDK:

from anthropic import Anthropic

client = Anthropic()
response = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0450 per call at standard rates
# Input:  $5.00/MTok
# Output: $25.00/MTok

How Claude Opus 4.8 compares on cost

Per-call cost for all models scoring 50+ on data extraction benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.002000/call (96% less, 89/100 quality).

What drives data extraction cost

Extraction is input-heavy and output-light (the raw document goes in, structured fields come out), which makes it one of the cheapest tasks per unit of value on this list. Output is small enough that output pricing is nearly irrelevant. Cost tracks document size, so the lever is sending only the pages that contain the fields you want.

For Claude Opus 4.8 specifically, that means output tokens cost 5.0x more than input, at $25.00 vs $5.00 per MTok. At this use case’s 4,000/1,000 token split, output accounts for 56% of the $0.0450 per-call cost.

Complete Claude Opus 4.8 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$5.004,000
Output$25.001,000

Prompt caching: 90% off input tokens

Caching drops input cost from $5.00 to $0.50/MTok. For repeated system prompts, that saves $0.0180 per call.

Batch API: 50% off all tokens

Submit requests asynchronously and receive 50% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.0450$450$270$180
50,000 calls$0.0450$2,250$1,350$900
100,000 calls$0.0450$4,500$2,700$1,800
500,000 calls$0.0450$22,500$13,500$9,000
1,000,000 calls$0.0450$45,000$27,000$18,000

Claude Opus 4.8 quality benchmarks for data extraction

Claude Opus 4.8 is a solid pick for data extraction

Scores 82/100 (rank #5 of 20). Good balance of quality and cost for data extraction.

Top-ranked: GPT 5.6 Terra (90/100) at $0.0200/call

Performance across all task types

Claude Opus 4.8 scores by task type. Data Extraction highlighted.

Reasoning97Code Generation95Code Review94Creative Writing93Summarization88Q&A85Extraction *82Classification80
Task typeConfidence scoreRank out of 20
Reasoning97/100#1
Code Generation95/100#1
Code Review94/100#2
Creative Writing93/100#1
Summarization88/100#4
Q&A85/100#5
Extraction(current page)82/100#5
Classification80/100#6

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

Alternative models for data extraction

13 models score 80+ on data extraction benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (96% less, 89/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Claude
GPT 5.6 LunaGPT$0.20$1.2089/100$0.00200096% cheaper
Gemini 3.5 Flash-LiteGemini$0.30$2.5083/100$0.00370092% cheaper
Gemini 3 FlashGemini$0.50$3.0086/100$0.00500089% cheaper
Claude Haiku 4.5Claude$1.00$5.0088/100$0.00900080% cheaper
Gemini 3.5 FlashGemini$1.50$9.0090/100$0.015067% cheaper
Claude Sonnet 5Claude$2.00$10.0088/100$0.018060% cheaper
GPT 5.6 TerraGPT$2.00$12.0090/100$0.020056% cheaper
Gemini 3.1 ProGemini$2.00$12.0085/100$0.020056% cheaper
GPT 5.4GPT$2.50$15.0089/100$0.025044% cheaper
Claude Sonnet 4.6Claude$3.00$15.0086/100$0.027040% cheaper
GPT 5.6 SolGPT$4.00$20.0088/100$0.036020% cheaper
GPT 5.5GPT$5.00$30.0087/100$0.050011% more
Claude Fable 5Claude$10.00$50.0085/100$0.0900100% more

About Claude Opus 4.8

Provider

Claude

Tier

Flagship

Context

200K tokens

Released

Apr 2026

Other models from Claude

ModelTierInput $/MTokOutput $/MTokContext
Claude Sonnet 4.6Mid-tier$3.00$15.00200K
Claude Haiku 4.5Fast / Budget$1.00$5.00200K
Claude Sonnet 5Mid-tier$2.00$10.00200K
Claude Opus 5Flagship$5.00$25.001,000K
Claude Fable 5.1Flagship$10.00$50.001,000K
Claude Fable 5Flagship$10.00$50.001,000K

You can compare Claude Opus 4.8 head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions

How much does Claude Opus 4.8 cost for data extraction per API call?

A typical data extraction call using Claude Opus 4.8 costs about $0.0450 per call. This estimate uses 4,000 input tokens and 1,000 output tokens at standard rates. Standard rates are $5.00 per million input tokens and $25.00 per million output tokens.

Is Claude Opus 4.8 the best model for data extraction?

Claude Opus 4.8 scores 82 out of 100 on data extraction benchmarks overall. It ranks #5 across all 20 models in our cross-provider registry. The highest-ranked model for this task is GPT 5.6 Terra from GPT. That model scores 90/100 on this task type. Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

What is the cheapest model for data extraction with good quality?

The most affordable model for data extraction above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 89/100. Switching from Claude Opus 4.8 to GPT 5.6 Luna saves about 96% per API call.

How can I reduce my Claude Opus 4.8 costs for data extraction?

Three strategies lower Claude Opus 4.8 costs for this task type effectively. Prompt caching gives a 90% discount on input tokens when reusing system prompts. The batch API gives 50% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.0450 to about $0.002250 per call.

How does Claude Opus 4.8 pricing compare to other Claude models?

Claude has 6 other models alongside Claude Opus 4.8 today: Claude Sonnet 4.6 at $3.00/$15.00 per million tokens (mid-tier), Claude Haiku 4.5 at $1.00/$5.00 per million tokens (fast / budget), Claude Sonnet 5 at $2.00/$10.00 per million tokens (mid-tier), Claude Opus 5 at $5.00/$25.00 per million tokens (flagship), Claude Fable 5.1 at $10.00/$50.00 per million tokens (flagship), Claude Fable 5 at $10.00/$50.00 per million tokens (flagship). The right choice depends on whether your data extraction workload prioritizes quality, cost, or speed.

What context window does Claude Opus 4.8 support?

Claude Opus 4.8 supports a context window of 200K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For data extraction, typical calls use 4,000 input and 1,000 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

Track what you spend on AI

This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.