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Claude · Flagship · 1,000K context window

Claude Opus 5 pricing for faq bot

$0.0275 per call at 1,500 input / 800 output tokens.

Per call

$0.0275

10K calls/mo

$275

Cache savings

90% off input

Batch savings

50% off all

Calculate your Claude Opus 5 costs

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

Configure your usage

1,500
100100K
800
5050K
10,000
1001M

Estimated cost

Monthly cost
$275
10,000 calls/month
Cost per call$0.0275
Daily cost$9
Input rate$5.00/MTok
Output rate$25.00/MTok
Analyze your real spend

Quick start

Call Claude Opus 5 with the Anthropic Python SDK:

from anthropic import Anthropic

client = Anthropic()
response = client.messages.create(
    model="claude-opus-5",
    max_tokens=800,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0275 per call at standard rates
# Input:  $5.00/MTok
# Output: $25.00/MTok

How Claude Opus 5 compares on cost

Per-call cost for all models scoring 50+ on faq bot benchmarks. Hover for details.

GPT 5.6 Luna$0.001260Gemini 3.5 Flash-Lite$0.002450Gemini 3 Flash$0.003150Claude Haiku 4.5$0.005500Gemini 3.5 Flash$0.009450Claude Sonnet 5$0.0110GPT 5.6 Terra$0.0126Gemini 3.1 Pro$0.0126GPT 5.4$0.0158Claude Sonnet 4.6$0.0165GPT 5.6 Sol$0.0220Claude Opus 4.8$0.0275GPT 5.5$0.0315Claude Fable 5$0.0550

Cheapest viable option: GPT 5.6 Luna at $0.001260/call (95% less, 85/100 quality).

What drives faq bot cost

The most bounded question-answering shape: a short question against a fixed knowledge base, with a short answer. Because the knowledge base never changes between calls, cache reads apply to nearly the entire input, and the effective cost per answer falls well below the list rate. A fast-tier model is usually sufficient when the answers are already written.

For Claude Opus 5 specifically, that means output tokens cost 5.0x more than input, at $25.00 vs $5.00 per MTok. At this use case’s 1,500/800 token split, output accounts for 73% of the $0.0275 per-call cost.

Complete Claude Opus 5 pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$5.001,500
Output$25.00800

Prompt caching: 90% off input tokens

Caching drops input cost from $5.00 to $0.50/MTok. For repeated system prompts, that saves $0.006750 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$0.0275$275$207.5$67.5
50,000 calls$0.0275$1,375$1,037.5$337.5
100,000 calls$0.0275$2,750$2,075$675
500,000 calls$0.0275$13,750$10,375$3,375
1,000,000 calls$0.0275$27,500$20,750$6,750

Claude Opus 5 quality benchmarks for faq bot

Benchmark data for faq bot is pending for Claude Opus 5. Test against your own evaluation suite before moving to production.

Performance across all task types

Claude Opus 5 scores by task type. FAQ Bot highlighted.

Task typeConfidence scoreRank out of 20

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 faq bot

13 models score 80+ on faq bot benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (95% less, 85/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Claude
GPT 5.6 LunaGPT$0.20$1.2085/100$0.00126095% cheaper
Gemini 3 FlashGemini$0.50$3.0082/100$0.00315089% cheaper
Claude Haiku 4.5Claude$1.00$5.0086/100$0.00550080% cheaper
Gemini 3.5 FlashGemini$1.50$9.0084/100$0.00945066% cheaper
Claude Sonnet 5Claude$2.00$10.0089/100$0.011060% cheaper
GPT 5.6 TerraGPT$2.00$12.0092/100$0.012654% cheaper
Gemini 3.1 ProGemini$2.00$12.0087/100$0.012654% cheaper
GPT 5.4GPT$2.50$15.0091/100$0.015843% cheaper
Claude Sonnet 4.6Claude$3.00$15.0088/100$0.016540% cheaper
GPT 5.6 SolGPT$4.00$20.0091/100$0.022020% cheaper
Claude Opus 4.8Claude$5.00$25.0085/100$0.0275same cost
GPT 5.5GPT$5.00$30.0090/100$0.031515% more
Claude Fable 5Claude$10.00$50.0088/100$0.0550100% more

About Claude Opus 5

Provider

Claude

Tier

Flagship

Context

1,000K tokens

Released

Jul 2026

Other models from Claude

ModelTierInput $/MTokOutput $/MTokContext
Claude Opus 4.8Flagship$5.00$25.00200K
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 Fable 5.1Flagship$10.00$50.001,000K
Claude Fable 5Flagship$10.00$50.001,000K

You can compare Claude Opus 5 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.

Claude Opus 5 pricing for other use cases

See how Claude Opus 5 costs change across different workload types.

Code Generation

$0.1100/call

Unit Test Generation

$0.1400/call

SQL Generation

$0.0325/call

API Generation

$0.1650/call

Code Refactoring

$0.1200/call

Code Review

$0.0750/call

PR Review

$0.1150/call

Security Review

$0.0925/call

Bug Detection

$0.0750/call

Document Summarization

$0.0750/call

PDF Summarization

$0.1125/call

Meeting Notes

$0.0900/call

Email Summarization

$0.0275/call

Chatbot

$0.0350/call

RAG Pipeline

$0.0675/call

Customer Support Bot

$0.0400/call

Data Extraction

$0.0450/call

JSON Extraction

$0.0350/call

Invoice Parsing

$0.0250/call

Resume Parsing

$0.0325/call

Chain of Thought

$0.1400/call

Legal Analysis

$0.1500/call

Math Reasoning

$0.0825/call

Financial Analysis

$0.1400/call

Content Moderation

$0.005000/call

Sentiment Analysis

$0.005000/call

Categorization

$0.007750/call

Intent Detection

$0.004000/call

Copywriting

$0.0525/call

Blog Writing

$0.2050/call

Marketing Copy

$0.0790/call

Product Descriptions

$0.0400/call

Related pages

Frequently asked questions

How much does Claude Opus 5 cost for faq bot per API call?

A typical faq bot call using Claude Opus 5 costs about $0.0275 per call. This estimate uses 1,500 input tokens and 800 output tokens at standard rates. Standard rates are $5.00 per million input tokens and $25.00 per million output tokens.

Is Claude Opus 5 the best model for faq bot?

Our benchmark data does not yet include a faq bot ranking for Claude Opus 5. We recommend testing it against your own evaluation criteria before production usage.

What is the cheapest model for faq bot with good quality?

The most affordable model for faq bot 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 85/100. Switching from Claude Opus 5 to GPT 5.6 Luna saves about 95% per API call.

How can I reduce my Claude Opus 5 costs for faq bot?

Three strategies lower Claude Opus 5 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 $0.0275 to about $0.001375 per call.

How does Claude Opus 5 pricing compare to other Claude models?

Claude has 6 other models alongside Claude Opus 5 today: Claude Opus 4.8 at $5.00/$25.00 per million tokens (flagship), 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 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 faq bot workload prioritizes quality, cost, or speed.

What context window does Claude Opus 5 support?

Claude Opus 5 supports a context window of 1,000K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For faq bot, typical calls use 1,500 input and 800 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

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