GPT-4.1 Mini vs GPT-5.2

OpenAI · US  |  OpenAI · US · Updated June 2026

Quick verdict

Both are OpenAI models. GPT-5.2 is the newer, generally stronger default; reach for GPT-4.1 Mini when its lower price or a specific cost or latency profile matters more than the latest capabilities.

GPT-4.1 Mini and GPT-5.2 are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. GPT-5.2 is a capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.

Key differences at a glance

Side-by-side specs

SpecGPT-4.1 MiniGPT-5.2
ProviderOpenAI (US) OpenAI (US)
ReleasedApril 14, 2025 December 11, 2025
Context window1M (~1,571 pages) 400K (~600 pages)
Price (in/out)$0.4/$1.6 per 1M tokens $1.75/$14 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image, code text, image, code
SWE-Bench Verified23.6% Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens

GPT-4.1 Mini

At $0.4/$1.6 per 1M tokens it undercuts GPT-5.2 ($1.75/$14 per 1M tokens), and that gap compounds at volume.

Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o

GPT-4.1 Mini

A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it runs cheaper at $0.4/$1.6 per 1M tokens.

Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini

GPT-4.1 Mini

A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it carries the larger 1M context.

Strong all-round reasoning

GPT-5.2

GPT-4.1 Mini is comparatively weak here — a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode

Reliable structured output

GPT-5.2

A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5 — and it is the newer of the two.

Broad ecosystem and tooling

GPT-5.2

GPT-5.2 lists broad ecosystem and tooling among its strengths; GPT-4.1 Mini does not.

Lowest cost at scale

GPT-4.1 Mini

At $0.4/$1.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

GPT-4.1 Mini

Its 1M window is about 2.6× larger than GPT-5.2's 400K, fitting roughly 1,571 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

GPT-4.1 Mini

At $0.4/$1.6 per 1M tokens it undercuts GPT-5.2, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

GPT-4.1 Mini

Larger 1M window fits more in one prompt.

Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens

GPT-4.1 Mini

It is specifically built for that.

Anyone whose priority is strong all-round reasoning

GPT-5.2

That is its strongest area.

GPT-4.1 Mini: where it fits

A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.

Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 out per million tokens, it sits in the budget price band.

GPT-5.2: where it fits

A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Released December 11, 2025 by OpenAI, it is built for strong all-round reasoning, reliable structured output, broad ecosystem and tooling, and professional workflows.

Its trade-offs: superseded by GPT-5.5, and smaller context than flagships. At $1.75 in / $14 out per million tokens, it sits in the mid price band.

The bottom line for this matchup

Because GPT-4.1 Mini and GPT-5.2 come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-5.2 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to GPT-5.2 and drop down only with a concrete reason.

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See pricing

Frequently asked questions

Is GPT-4.1 Mini or GPT-5.2 better for coding?

Public SWE-Bench figures are not available for GPT-5.2, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens while GPT-5.2 leans toward strong all-round reasoning, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GPT-4.1 Mini or GPT-5.2?

GPT-4.1 Mini is cheaper — $0.4/$1.6 per 1M tokens vs $1.75/$14 per 1M tokens, roughly 4.4× apart on input.

Which has the bigger context window?

GPT-4.1 Mini — 1M vs 400K, about 2.6× larger. Useful only if the model actually reasons over the full window, which not all do.

Should I upgrade from GPT-4.1 Mini to GPT-5.2?

Since both are OpenAI models, the newer one (GPT-5.2) is usually the better default unless you need a specific cost or latency profile from the other.

Which is newer, GPT-4.1 Mini or GPT-5.2?

GPT-5.2 — released December 11, 2025, about 8 months after GPT-4.1 Mini.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.