OpenAI Model Pricing Guide: GPT-5 vs GPT-4.1 for Agentic AI

If you are trying to choose the best OpenAI model for an AI agent, the first question is usually not raw intelligence.

It is cost.

More specifically:

Which OpenAI model is cheap enough to use at scale, but still strong enough to handle real agentic work?

That is the practical buying question behind terms like:

• OpenAI model pricing
• GPT-5 vs GPT-4.1
• best OpenAI model for AI agents
• cheapest OpenAI model for automation
• which model should I use for subagents, routing, extraction, or coding

This guide is built to answer that question clearly.

All prices and model descriptions below were checked against official OpenAI API docs on March 24, 2026. One important clarification up front: people often search for models like GPT-5.1 mini or GPT-5.1 nano, but OpenAI's public general-purpose lineup currently lists GPT-5.1, GPT-5 mini, GPT-5 nano, GPT-5.4, GPT-5.4 mini, and GPT-5.4 nano instead.

The quick answer

If you only need the short version:

• Cheapest overall: GPT-5 nano
• Best cheap general-purpose model: GPT-5 mini
• Best current frontier model for agentic and professional workflows: GPT-5.4
• Best mini model for subagents and coding-heavy workflows: GPT-5.4 mini
• Best non-reasoning GPT-4 family option: GPT-4.1
• Model to avoid for most production cost profiles: GPT-4.5 Preview, because it is deprecated and dramatically more expensive

OpenAI model pricing table

Prices below are for text tokens and shown per 1 million tokens.

Model	Positioning	Input	Cached input	Output	Best fit
GPT-5.4	Flagship frontier model	$2.50	$0.25	$15.00	High-stakes agentic workflows, advanced coding, professional work
GPT-5.4 mini	Strongest mini in the 5.4 line	$0.75	$0.075	$4.50	Coding agents, computer use, subagents
GPT-5.4 nano	Cheapest 5.4-class model	$0.20	$0.02	$1.25	Classification, extraction, ranking, high-volume agent steps
GPT-5.2	Previous frontier professional model	$1.75	$0.175	$14.00	Older 5.x frontier deployments not yet moved to 5.4
GPT-5.1	Best model for coding and agentic tasks in its generation	$1.25	$0.125	$10.00	Serious coding and agent workflows with configurable reasoning
GPT-5	Previous reasoning model	$1.25	$0.125	$10.00	Existing GPT-5 deployments that have not upgraded to 5.1
GPT-5 mini	Cost-efficient general 5.x model	$0.25	$0.025	$2.00	Cheap general agent work, prompt-driven workflows
GPT-5 nano	Cheapest 5.x model	$0.05	$0.005	$0.40	Ultra-cheap routing, summarization, tagging, simple automation
GPT-4.5 Preview	Deprecated large model	$75.00	$37.50	$150.00	Rare research comparison only
GPT-4.1	Smartest non-reasoning GPT-4.1 model	$2.00	$0.50	$8.00	Tool calling and instruction following without a reasoning step
GPT-4.1 mini	Smaller, faster GPT-4.1	$0.40	$0.10	$1.60	Lower-cost GPT-4.1 workloads
GPT-4.1 nano	Cheapest GPT-4.1 model	$0.10	$0.025	$0.40	Fast low-cost 4.x automation and routing

What each model is good at

Pricing alone is not enough. For agentic AI, the better question is what each model is optimized to do.

GPT-5.4

OpenAI describes GPT-5.4 as its best intelligence at scale for agentic, coding, and professional workflows. This is the model to reach for when:

• the workflow is long and multi-step
• tool use quality matters
• the cost of a bad plan is much higher than the cost of extra tokens
• you need a frontier model to coordinate tools, subagents, and deep reasoning

For enterprise agents, this is the premium option.

GPT-5.4 mini

This is probably the most interesting model in the current lineup for production builders. OpenAI positions it as its strongest mini model for coding, computer use, and subagents.

That matters because many agent systems do not need the absolute top model on every step. They need a model that is:

• reliable with tools
• much cheaper than the flagship
• still capable enough to run repeated agent loops

For many agentic AI systems, GPT-5.4 mini is the model that lets you keep quality reasonably high without paying frontier-model prices on every turn.

GPT-5.4 nano

This is not the cheapest OpenAI model overall, but it is the cheapest model in the 5.4 generation. OpenAI explicitly calls out use cases like:

• classification
• data extraction
• ranking
• subagents

That makes it a strong fit for high-volume pipelines where each call is narrow and structured.

GPT-5.1

OpenAI describes GPT-5.1 as the best model for coding and agentic tasks in that generation. It still matters because many teams compare it directly against GPT-5.4.

If you already built around GPT-5.1, the model is still strong. But if you are starting fresh and want the current frontier recommendation, OpenAI now points builders toward GPT-5.4.

GPT-5 and GPT-5.2

These are best understood as previous generation reference points inside the 5.x family.

• GPT-5 is the older reasoning model in the family
• GPT-5.2 is the previous frontier professional model before GPT-5.4

They are useful in migration discussions, but not usually the first recommendation for new projects.

GPT-5 mini

GPT-5 mini is the practical budget choice for many teams. OpenAI positions it as a faster, more cost-efficient version of GPT-5, and says it is great for well-defined tasks and precise prompts.

That makes it attractive for:

• support automation
• triage
• policy checks
• deterministic prompt chains
• mid-quality agent orchestration where cost matters

If someone asks for the best cheap OpenAI model for an AI agent, this is often the safest first answer.

GPT-5 nano

This is the cheapest current general-purpose GPT-family model in the official docs. OpenAI describes it as great for summarization and classification.

That means it is ideal for:

• intent routing
• tagging
• short summaries
• extraction from structured documents
• guardrail checks
• lightweight subagent steps

For agentic systems, GPT-5 nano is usually not the model that should own the entire workflow. It is the model that should handle the boring high-volume pieces around the workflow.

GPT-4.1

The GPT-4.1 family still matters because it is positioned differently from the GPT-5 line. OpenAI calls GPT-4.1 the smartest non-reasoning model and highlights:

• instruction following
• tool calling
• broad knowledge across domains
• low latency without a reasoning step

That makes it relevant when you want strong capability but do not want a reasoning-style model on the path.

GPT-4.1 mini and GPT-4.1 nano

These are still viable, but OpenAI's own docs increasingly point people toward the GPT-5 equivalents for more complex tasks:

• GPT-4.1 mini is a smaller, faster GPT-4.1 model
• GPT-4.1 nano is the fastest and cheapest model in the 4.1 family

If you are already using them, they are not broken. But for new builds, the GPT-5 family is usually the more interesting comparison.

GPT-5 vs GPT-4.1: what actually changed for buyers?

The simplest way to think about it is this:

• The GPT-4.1 family is the strong non-reasoning line.
• The GPT-5 family is the stronger reasoning and agentic line.
• The GPT-5.4 line is the current frontier recommendation.

For many teams, the pricing comparison is enough to force a rethink.

GPT-5 nano vs GPT-4.1 nano

• GPT-5 nano input is cheaper: $0.05 vs $0.10
• output is the same: $0.40 vs $0.40

If your workload is mostly routing, extraction, or short classification, GPT-5 nano is hard to ignore.

GPT-5 mini vs GPT-4.1 mini

• GPT-5 mini input is cheaper: $0.25 vs $0.40
• GPT-5 mini output is higher: $2.00 vs $1.60

That means GPT-5 mini is not strictly cheaper on every dimension, but it is often a better cost-capability tradeoff if your workflow is prompt-heavy and output-light.

GPT-5.4 mini vs GPT-4.1 mini

• GPT-5.4 mini is materially more expensive
• but it is positioned for stronger coding, subagents, and computer use

This is the classic agentic AI tradeoff: pay more per call, or pay less and compensate with more retries, more guardrails, or more human intervention.

The best OpenAI model for agentic AI by use case

Here is the practical routing logic.

Use GPT-5 nano when:

• you need the cheapest possible model
• each task is narrow and easy to verify
• you are building routing, extraction, tagging, or summarization layers

Use GPT-5 mini when:

• you want a cheap default model for many workflows
• your prompts are fairly structured
• you need more capability than nano, but want to stay cost-sensitive

Use GPT-5.4 nano when:

• you want a 5.4-generation model
• you need better modern agent behavior than older nano options
• the job is still simple and high-volume

Use GPT-5.4 mini when:

• you are running many subagents
• the model must use tools well
• coding or computer-use quality matters
• you need a better mini model, not the absolute flagship

Use GPT-5.4 when:

• the workflow is expensive if it fails
• the model is planning across many steps and systems
• you want the strongest current OpenAI model for professional and agentic work

Use GPT-4.1 only when:

• you specifically want a strong non-reasoning model
• you have existing 4.1 tuning or evaluation infrastructure
• you prefer the 4.1 behavior profile for a known workflow

A better way to budget for AI agents

Most teams make the same mistake: they try to pick one model for the entire agent.

That is usually the wrong architecture.

A better design is a tiered model stack:

• use GPT-5 nano or GPT-5.4 nano for intake, routing, and extraction
• use GPT-5 mini for the bulk of repeatable task handling
• escalate only hard cases to GPT-5.4 mini or GPT-5.4

This matters because agentic systems are rarely one prompt. They are pipelines:

1. classify the request
2. gather context
3. decide whether a tool should run
4. execute a structured action
5. summarize the result
6. escalate edge cases

Not every step deserves flagship-model pricing.

What we would recommend for most teams

If you are choosing today and want a practical default:

• Start with GPT-5 mini for cheap general-purpose work.
• Use GPT-5 nano for ultra-cheap support tasks around the main workflow.
• Move up to GPT-5.4 mini for coding-heavy or subagent-heavy systems.
• Reserve GPT-5.4 for the steps where mistakes are expensive.

That is usually a more defensible production strategy than forcing one expensive model to do everything.

Final takeaway

The most important pricing insight is not that OpenAI has more models now.

It is that the pricing ladder is much more useful for agentic AI system design:

• GPT-5 nano is the cheapest current general-purpose entry point
• GPT-5 mini is often the strongest cost-performance default
• GPT-5.4 mini is the mini model many serious agent builders should evaluate
• GPT-5.4 is the premium model for complex professional workflows

If you are still testing with GPT-4.1 mini, the right next comparison is usually not GPT-4.5 Preview.

It is:

• GPT-5 mini for cheap general workloads
• GPT-5 nano for ultra-low-cost steps
• GPT-5.4 mini for better agent quality

Sources

• OpenAI API pricing
• OpenAI models overview
• GPT-5.4 model page
• GPT-5.4 mini model page
• GPT-5.4 nano model page
• GPT-5.1 model page
• GPT-5 model page
• GPT-5.2 model page
• GPT-5 mini model page
• GPT-5 nano model page
• GPT-4.1 model page
• GPT-4.1 mini model page
• GPT-4.1 nano model page
• GPT-4.5 Preview model page