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LOW-COST GPT400K CONTEXTTEXT + VISIONPROMPT CACHINGBATCH -50%

GPT-5.4 nano API Pricing

OpenAI's cheapest GPT-5.4-class model for simple high-volume tasks: $0.20/M input, $1.25/M output, and $0.02/M cached input. It is built for classification, extraction, ranking, routing, and small subagents where cost matters more than maximum capability.

Input - per 1M tokens
$0.20/M
Standard model tier standard
Output - per 1M tokens
$1.25/M
Batch/Flex output is $0.625/M standard
Cached input - 90% off
$0.02/M
Prompt cache hit price -90%
Effective - agentic blend
$0.15/M
92/8 split - 82% cache
§ 01 / TERMINAL

Run the numbers.

Live calculator pre-loaded with current GPT-5.4 nano rates. Use it for high-volume routing, extraction, and classification workloads where small cost differences compound quickly.

$ /mo
Workload split
Prompt cache hit rate
Tokens you can process
Words equivalent (English)
Effective rate
§ 02 / SCENARIOS

Real-world presets.

§ 03 / TAPE

Price history.

API list price is still $0.20/M input and $1.25/M output since the first GPT-5.4 nano snapshot.

Input · $0.20/M
Output · $1.3/M
Cached · $0.02/M
MAR 17 First listed snapshot at $0.20/M input and $1.25/M outputMAY 18 Verified unchanged on OpenAI pricing docs
§ 04 / TOKENIZER

Paste text. See tokens. See cost.

Estimate · tiktoken-o200k_base · ≈3.85 chars/token Auto-counts as you type

This is a chars-per-token approximation, not a real tokenizer. Actual tokens vary by language, code density, and tool-call overhead — counts are typically ±10–20% off for English prose, more for code or non-Latin scripts. For exact billing, use the vendor's official tokenizer.

Characters
Words
Tokens (estimated)
Cost as input · uncached
Cost as output · uncached
Cost as cached input
§ 05 / SHELF

Up against the shelf.

All models →
Model Input /M Output /M Effective blended Context Best for
GPT-5.4 nano Current $0.20 cache $0.02 $1.25 $0.15 agentic 92/8 400K Classification and extraction
GPT-5.4 mini $0.75 cache $0.07 $4.50 $0.54 more capable 400K Subagents and computer-use tasks
GPT-5.4 $2.50 cache $0.25 $15.00 $1.80 larger model 1.05M Affordable OpenAI frontier work
GPT-5.3-Codex $1.75 cache $0.17 $14.00 $1.54 coding specialist 400K Agentic coding tasks
Gemini 2.5 Pro $1.25 cache $0.13 $10.00 $1.10 tier 1 pricing 2M Large multimodal context
DeepSeek V4 Pro $0.43 cache $0.00 $0.87 $0.14 promo price 1M Low-cost reasoning workloads
DeepSeek V4 Flash $0.14 cache $0.00 $0.28 $0.05 same blend 1M Bulk low-cost traffic

Frequently asked.

Practical GPT-5.4 nano pricing questions, with OpenAI's published rates separated from workload assumptions.

Q · 01 What is the standard GPT-5.4 nano API price? +
OpenAI lists gpt-5.4-nano at $0.20/M input tokens, $0.02/M cached input tokens, and $1.25/M output tokens. This page stores the public list price in USD and marks the source as OpenAI's pricing docs.
Q · 02 How much cheaper is GPT-5.4 nano than GPT-5.4 mini? +
Under the shared 92/8 agentic blend with 82% cache hits, GPT-5.4 nano is about $0.15/M while GPT-5.4 mini is about $0.54/M. That makes nano roughly 3.6x cheaper for the same token mix.
Q · 03 How much cheaper are Batch and Flex? +
OpenAI lists Batch and Flex for gpt-5.4-nano at half the standard rate: $0.10/M input, $0.01/M cached input, and $0.625/M output. That is the best fit for latency-tolerant bulk classification or extraction.
Q · 04 Is Priority pricing available for GPT-5.4 nano? +
No Priority row is listed for gpt-5.4-nano on OpenAI's pricing page. The Priority table lists gpt-5.5, gpt-5.4, and gpt-5.4-mini, so this page does not publish a Priority rate for nano.
Q · 05 Does GPT-5.4 nano have regional pricing? +
Yes. OpenAI states that regional processing/data-residency endpoints carry a 10% uplift for gpt-5.4-nano and related GPT-5.4/5.5 models. Standard global routing uses the public standard rate.
Q · 06 Does GPT-5.4 nano support computer use? +
No. OpenAI's model page lists computer use as Not supported for gpt-5.4-nano. Use GPT-5.4 mini or GPT-5.4 when browser or desktop automation is part of the workload.
Q · 07 What release date is used here? +
OpenAI's model page lists the first GPT-5.4 nano snapshot as gpt-5.4-nano-2026-03-17. This page uses 2026-03-17 as the model release date for pricing-history purposes.
Q · 08 How accurate is the tokenizer estimate? +
The live widget uses an estimated 4.875 characters per token for English text and labels the tokenizer as tiktoken-o200k_base. It is good for budget planning, but exact billing can differ by language, whitespace, code, tool calls, and image inputs.