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OpenAI: GPT-4o (batch) API Pricing

OpenAI: GPT-4o (batch) costs $1.25 per 1M input tokens and $5.00 per 1M output tokens (cache reads: $0.625). Context window: 128K. Prices verified 2026-10-21 · source

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Alternatives to consider

🏠 Same provider
OpenAI: gpt-oss-20b
$0.018 in / $0.090 out
Quality score: 10

Cheapest openai model — 98% less per month

Price history
2026-08-23 → 2026-10-21 · 59 daily snapshots
inputoutput

Rebuilt daily from our snapshot archive — the chart appears once a model has 5+ snapshots of history.

Pricing behavior
Stable — no price moves across our 59 daily snapshots (2026-08-23 → 2026-10-21).

From our own daily snapshot archive — independent of provider announcements.

Input / 1M tokens
$1.25
Output / 1M tokens
$5.00
Context window
128K
Max output
16K

Token economics

Token typePricevs base input
Standard input$1.25—
Cache read$0.625−50%
Output$5.00—
Web search tool$10/1k searches—

Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.

Knowledge cutoff
2023-10-31

Training data ends here — newer events require retrieval or web search.

What would OpenAI: GPT-4o (batch) cost you per month?

WorkloadRequests/moAvg tokens (in/out)Est. monthly cost
Light chatbot10,000800 / 400$30.00
Coding agent5,0008,000 / 2,000$100.00
RAG pipeline30,0004,000 / 500$225.00
Doc summarizer2,00020,000 / 1,000$60.00

Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.

About OpenAI: GPT-4o (batch)

GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...

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Frequently asked questions

How much does OpenAI: GPT-4o (batch) cost?

OpenAI: GPT-4o (batch) costs $1.25 per 1M input tokens and $5.00 per 1M output tokens; cached input tokens cost $0.625 per 1M. Verified 2026-10-21 — provider source.

What is the context window?

128K tokens, with up to 16K output tokens per response. That's roughly 160 pages of text in a single request.

Does it support prompt caching?

Yes — cached input is $0.625/1M, about 50% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.

What's a cheaper alternative?

ScaleDown: Summarize saves about 99% on a typical workload with comparable quality.

Official resources