GPT-5.2 wins on coding (85 vs 78) and writing quality and context window (200K vs 128K). GPT-5.2 Mini wins on price ($1.2 vs $1.75/1M input). For most workflows, GPT-5.2 is the stronger default — capable but outclassed — gpt-5.4 is now cheaper and better.
The safest GPT-5.2 vs GPT-5.2 Mini default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
GPT-5.2 is the strongest answer here for GPT-5.2 vs GPT-5.2 Mini — pick it when quality of output matters more than the $1.75/1M/1M input you pay for it.
GPT-5.2 Mini handles the same job for about 62% less per token. Start here and only move up if the output is not good enough.
GPT-5.2 Mini is the fastest of these for GPT-5.2 vs GPT-5.2 Mini — worth it when latency is what the reader notices, not the last few points of reasoning depth.
GPT-5.2 leads on coding with a score of 85 vs 78 for GPT-5.2 Mini.
GPT-5.2 has the larger context window: 200K vs 128K for GPT-5.2 Mini.
GPT-5.2 Mini is cheaper at $1.2/1M input tokens vs $1.75/1M for GPT-5.2.
Choose GPT-5.2 for serious coding and complex product work. Its coding and research scores are what carry the recommendation here.
Choose GPT-5.2 Mini when your work is mostly budget technical workflows and high-volume product integrations — that is the workload it was tuned for.
GPT-5.2 Mini is the more cost-efficient option at $1.2/1M input — GPT-5.2 costs 1x more per input token, so the gap is worth taking seriously wherever token volume rather than peak quality drives the bill.
Switch the scoring lens to see whether the GPT-5.2 vs GPT-5.2 Mini answer changes when cost, speed, or long-document depth leads the decision.
OpenAI / Premium / Sep 3, 2026
Capable but outclassed — GPT-5.4 is now cheaper and better.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You're starting a new project — GPT-5.4 is cheaper and more capable.
Where the GPT-5.2 vs GPT-5.2 Mini recommendation shifts once you weigh price or latency differently.
Capable but outclassed — GPT-5.4 is now cheaper and better.
Solid OpenAI budget option, though Gemini Flash offers better value.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GPT-5.2OpenAI | $1.75/1M | $14.00/1M | $46 | 200k tokens | Balanced | 85 | 82 | 84 |
| GPT-5.2 MiniOpenAI | $1.20/1M | $4.80/1M | $22 | 128k tokens | Fast | 78 | 72 | 68 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for GPT-5.2 vs GPT-5.2 Mini, what it is genuinely good at, and where we would steer you away from it.
The default answer for GPT-5.2 vs GPT-5.2 Mini — 85/100 on the coding axis, and the model we would start with unless the price below rules it out.
Reliable OpenAI flagship for serious coding and product work — a strong default before GPT-5.4 was released.
You're starting a new project — GPT-5.4 is cheaper and more capable.
Still capable but GPT-5.4 at $2.50/1M input is now cheaper and better. Hard to justify GPT-5.2 at $12/1M for new projects.
Full pricing, benchmark table and release notes on the GPT-5.2 page.
Where most budgets should land for GPT-5.2 vs GPT-5.2 Mini — about 62% less per token than GPT-5.2, and still 78/100 on the coding axis.
Lower-cost OpenAI model that keeps a solid balance of usefulness, speed, and affordability for everyday tasks.
Cost is your primary concern — Gemini 3.1 Flash offers more for less.
A decent budget OpenAI pick, but Gemini 3.1 Flash undercuts it on price with a larger context window.
Full pricing, benchmark table and release notes on the GPT-5.2 Mini page.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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GPT-5.2 wins on more of the categories we score — coding, research, reasoning — so it is the better default of the two. GPT-5.2 Mini is the better pick when your work is mostly budget technical workflows and high-volume product integrations. Neither is universally "better": GPT-5.2 is aimed at serious coding and complex product work, GPT-5.2 Mini at budget technical workflows and high-volume product integrations.
GPT-5.2 Mini is cheaper at $1.2/1M input and $4.8/1M output. GPT-5.2 costs $1.75/1M input and $14/1M output.
GPT-5.2 has the larger context window at 200K tokens vs GPT-5.2 Mini's 128K. For large document analysis, GPT-5.2 is the stronger pick.
GPT-5.2 is better for coding with a score of 85 vs GPT-5.2 Mini's 78 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
GPT-5.2 Mini is faster with a fast speed rating (score: 4) vs GPT-5.2's balanced rating (score: 3). Speed matters most for interactive and high-throughput work; for batch jobs the GPT-5.2 latency penalty is usually invisible.
Superseded by GPT-5.4 for most use cases. Claude Sonnet 4.6 leads on both coding and writing quality. Avoid it if you're starting a new project — GPT-5.4 is cheaper and more capable. That is the main case for looking at GPT-5.2 Mini instead.
Weaker on nuanced reasoning than premium models. Gemini 3.1 Flash is now cheaper with a larger context window. Avoid it if cost is your primary concern — Gemini 3.1 Flash offers more for less. Against GPT-5.2 specifically, the gap shows up most on coding (85 vs 78).
Take a moderate workload of 10M input and 2M output tokens a month. GPT-5.2 runs $45.50 (at $1.75/1M in and $14/1M out); GPT-5.2 Mini runs $21.60 (at $1.2/1M in and $4.8/1M out). That is a $23.90/month difference — GPT-5.2 Mini is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is GPT-5.2 for serious coding and complex product work, with GPT-5.2 Mini handling budget technical workflows and high-volume product integrations. Routing high-volume, low-stakes calls to GPT-5.2 Mini at $1.2/1M and reserving GPT-5.2 for the hard cases is usually the cheapest arrangement that does not cost you quality.