At a glance

GPT-4.1 from OpenAI is a mid-tier model priced at US$2.00 per 1M input tokens and US$8.00 per 1M output tokens. For a typical solo-developer workload (8 hours/day, 22 days/month — 1 medium feature, 5 small bug fixes, 4 PR reviews, 2 stack-trace debugs, ~1500 lines of TypeScript, 1 large-doc read, with prompt caching at the default mix) GPT-4.1 costs about US$39/month. The 1,000K-token context window covers most monorepo scans without truncation.

What does your monthly budget buy?

Move the slider or switch task mix — values update live.

Monthly budget

US$100 / month

≈ $23/wk · ≈ $4.55/day

on GPT-4.1

Task mix

Input tokens

68.0M

Output tokens

1.9M

Total tokens

69.9M

Per month this budget delivers

  • Medium feature (10–15 files)155
  • PR review1,869
  • Lines of TypeScript452,488
  • Small bug fix2,123
  • Work email40,000
  • Unit test file1,508
Open in the full calculator

How does this model compare on price?

Input vs output per 1M tokens

Hover a row to compare input vs output rates.
  • GPT-4.1
    US$2.00
    US$8.00
  • Mid-tier median (other mid models)
    US$2.00
    US$10.00
  • Cheapest in catalog (Gemini 2.0 Flash)
    US$0.10
    US$0.40
Input per 1MOutput per 1M

Cost per task

At the default coding-agent mix with 50% cache hits.

USD per single task

Hover a bar to see per-task cost detail.
  • Lines of TypeScript
    US$0.0002
  • Small bug fix
    US$0.0471
  • PR review
    US$0.0535
  • Read a large doc
    US$0.0745
  • Debug from stack trace
    US$0.0969
  • Refactor a module (8–12 files)
    US$0.46
  • Medium feature (10–15 files)
    US$0.64
  • Onboard to a new repo
    US$0.80

Typical developer day

The 22-day month is based on the median working-day count across DE/US.

ActivityCountPer taskDailyMonthly
Medium feature (10–15 files)1US$0.64US$0.64US$14.11
Small bug fix5US$0.05US$0.24US$5.18
PR review4US$0.05US$0.21US$4.71
Debug from stack trace2US$0.10US$0.19US$4.26
Read a large doc1US$0.07US$0.07US$1.64
Micro-interaction (explain / lint fix)30US$0.00US$0.09US$1.88
Lines of TypeScript1,500US$0.00US$0.33US$7.29
TotalUS$1.78US$39.07

The 1500-lines-of-TS row models ~1000 lines read (cache-hit) + ~500 lines written. Headline figures are precise to ~5% — see the FAQ.

Monthly cost matrix

What each monthly budget buys on this model (typical solo-developer day, 22 working days).

Monthly budgetMedium featuresPR reviewsDebug sessionsLines of TS
Typical (≈ $39)60730403176,791
$50/month77934516226,244
$200/month3113,7382,065904,977
$500/month7799,3455,1622,262,443
$2000/month3,11837,38320,6509,049,773

Typical mix: coding-agent (85% input, 50% cache hits). Values show the maximum count of each task type at that budget.

What this model can do

  • Coding

    Trained or post-trained for code generation tasks.

  • Reasoning

    Not supported

  • Multimodal

    Accepts images alongside text.

  • Prompt cache

    Cache reads billed at ~10% of input price — cuts agent costs sharply.

  • Batch API

    50% off when you accept up to 24-hour turnaround.

  • Tool use

    Native function-calling / tool-use API support.

  • Long context

    ≥ 200K-token context window.

  • Extended thinking

    Not supported

When does this model fit?

Best for

  • Long-context retrieval over very large codebases
  • Stable instruction-following workflows that don't benefit from reasoning
  • Reproducibility — pinned model that won't shift behavior

Watch out for

  • GPT-5-mini at $0.25/1M input is usually a better value — only pick 4.1 if pinned
  • No extended-thinking mode means complex bugs may slip past

OpenAI in the catalog

Total models

6

Median input/1M

US$1.63

Median output/1M

US$8.00

Input range

US$0.25–US$2.50

Related models

Sources

Frequently asked questions about GPT-4.1

What does a typical month on GPT-4.1 cost?

Running the realistic solo-developer day (1 medium feature + 5 small bug fixes + 4 PR reviews + 2 debug sessions + ~1500 lines of TypeScript + 1 large-doc read, 22 working days) on GPT-4.1 costs about US$39/month. Heavier workloads scale proportionally; lighter workloads cost less.

How big is GPT-4.1's context window?

1,000K tokens total, with up to 32K of output. That fits whole repository snapshots, tests included in a single call.

Why is GPT-4.1 output priced so much higher than input?

Providers charge US$8.00 per 1M output tokens against US$2.00 per 1M input — output requires real compute, input comes mostly from cache. Coding agents read many files (input-heavy) and emit compact diffs (low output), so total spend is usually input-driven.

How much does prompt caching save on GPT-4.1?

Cache reads typically cost only 10% of the regular input rate. On a coding-agent mix with 50% cache hits, that saves roughly 45% on input — which is about 38% off your total bill on input-heavy workloads. Anthropic models charge a one-time cache-write surcharge (25% over input) that pays for itself after 2–3 hits.

Is GPT-4.1's batch API worth using?

Yes, if you can tolerate up to 24-hour turnaround: batch input/output are 50% cheaper than real-time rates. Perfect for nightly code reviews, bulk refactors or pre-merge analysis — wrong for inner-loop editing where you need an answer in seconds.

Try GPT-4.1 pricing live

Open the full calculator with your own budget, task mix and region (US or DE with 19% VAT).

Open calculator