Claude vs GPT API for Automation (2026): Which Should You Build On?

🔄 Updated September 2026

Quick Answer: Pick by tier, not by brand. For high-volume parsing and routing, GPT-6 Luna ($0.10/$0.50 per million tokens) is far cheaper than Claude Haiku 4.5 ($1/$5). For agents, Claude Sonnet 5 and GPT-6 Sol are the same price ($2/$10), so test both on your workflow. For the hardest reasoning and computer use, Claude Opus 5.5 ($4/$20) costs less than GPT-6 Astra ($10/$50).

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Both Anthropic and OpenAI shipped new models in September 2026, and the price gaps between them have changed completely. This guide compares current API pricing tier by tier and recommends a model for each type of automation workflow.

Current API Prices, Tier by Tier

Tier	Claude	Price (input / output per 1M tokens)	GPT	Price (input / output per 1M tokens)
High-volume	Haiku 4.5	$1 / $5	GPT-6 Luna	$0.10 / $0.50
Workhorse	Sonnet 5	$2 / $10	GPT-6 Sol	$2 / $10
Flagship	Opus 5.5	$4 / $20	GPT-6 Astra	$10 / $50
Top reasoning	Fable 5.1	$10 / $50	—	—

Prices as of September 2026. Check Anthropic’s pricing page and OpenAI’s pricing page before budgeting.

Context windows: Claude Opus 5.5, Fable 5.1, Opus 5 and Sonnet 5 support 1M-token context. GPT-6 Sol and Luna carry about 1.05M tokens.

The Discounts That Change the Real Bill

Caching. Most current Claude models charge 10% of the input price for cached reads. Opus 5.5’s cache reads cost $0.20 per million tokens (5% of input), and Fable 5.1’s cost $0.25 (2.5%). On OpenAI’s side, GPT-6 Sol’s cached input is $0.20 and Luna’s is $0.01.

Batch processing. Both companies discount batch jobs by 50%. That’s ideal for nightly processing that doesn’t need instant answers.

Long prompts. OpenAI bills prompts over 272,000 input tokens on GPT-6 Sol at twice the input rate and 1.5× the output rate. Claude 4.6 and later models bill 1M-token context at standard pricing.

Token counts aren’t equal. Anthropic says Claude 4.7 and later models use a tokenizer that produces about 30% more tokens for the same text. Compare cost per task on your real prompts, not price per token.

Which Model for Which Workflow

Workflow	Recommended	Why
Email parsing, classification, data extraction	GPT-6 Luna	Roughly 10× cheaper than Haiku per token, and built for high-volume, clear-goal tasks
AI agents with tool calls (n8n, Make)	Claude Sonnet 5 or GPT-6 Sol	Same list price. Run your workflow on both and compare errors
Long documents and knowledge bases	Sonnet 5 or Sol	Both handle 1M-token context
Computer use and browser agents	GPT-6 Astra or Claude Opus 5.5	Astra is OpenAI’s strongest model for computer use. Opus 5.5 beats Astra on some coding and knowledge-work benchmarks at a much lower price
Hardest long-running agent work	Claude Fable 5.1	Anthropic’s recommended step up when Opus 5.5 at higher effort isn’t enough

How to Choose Without Guessing

1. Start cheap. Run your workflow on the lowest tier that might work (Luna or Haiku), then move up only for steps that fail.
2. Route by difficulty. In n8n, send routine requests to a cheap model and escalate only failures to a flagship. Our multi-model agent patterns guide shows how.
3. Measure cost per completed task, not per token. A cheaper model that fails more often and needs retries can cost more overall.

The Verdict

• Choose GPT-6 Luna if your priority is the lowest cost for high-volume extraction and routing.
• Choose Claude Sonnet 5 or GPT-6 Sol for everyday agent work. Pick the one that makes fewer mistakes on your own workflow.
• Choose Claude Opus 5.5 if you need flagship reasoning at the lowest flagship price.
• Choose GPT-6 Astra if computer use is the core of your automation and budget is secondary.

Not sure you need the API at all? Compare Claude for small business vs building your own automation. For more on OpenAI’s newest models, see what GPT-6 Astra means for automation builders.

FAQ

Is Claude or GPT cheaper for automation?

It depends on the tier. OpenAI is much cheaper at the high-volume tier (Luna vs Haiku). The workhorse tier is the same price (Sonnet 5 vs Sol). Claude is cheaper at the flagship tier (Opus 5.5 vs Astra).

What’s the cheapest model for n8n workflows?

GPT-6 Luna, at $0.10 per million input tokens and $0.50 per million output tokens. It’s built for simple, high-volume tasks like extraction and summaries.

Which is better for AI agents, Claude Sonnet 5 or GPT-6 Sol?

They cost the same, so test both. Run the same agent workflow on each for a day and compare completed tasks and errors.

Does prompt caching make a big difference?

Yes, for workflows that resend the same instructions or documents. Cached reads cost a fraction of normal input on both platforms, which can cut input costs dramatically.

Are these prices permanent?

No. Both companies changed prices in September 2026. Re-check official pricing pages before any large build.