Migration assistant

Replacing GPT-4 32K?

Ranked replacement candidates, each shown with exactly what changes if you switch. Same-provider matches surface first because switching cost is lower; capability regressions are flagged in red.

OP
Migrating from

GPT-4 32K

OpenAI · Active
Input: $0.06/M Output: —/M Context: 32K
View detail →
#1 RECOMMENDED

GPT-5 Nano

OpenAI · GPT-5
same provider; 17% cheaper input; 400K context (larger)
View full detail →
What changes if you switch
Field GPT-4 32K → GPT-5 Nano Impact
Input price $0.06/M → $0.05/M Save 17%
Output price — → $0.4/M Source price not verified
Context window 32K tokens → 400K tokens +1150% larger
Lifecycle Active → Active Same status
Other candidates
#2

GPT-4.1 Mini

OpenAI
same provider; 567% more expensive input; 1M context (larger)
Details →
Input price: +567% more expensiveContext window: +3174% larger
#3

GPT-4.1 Nano

OpenAI
same provider; 67% more expensive input; 1M context (larger)
Details →
Input price: +67% more expensiveContext window: +3174% larger
#4

GPT-4o Mini

OpenAI
same provider; 150% more expensive input; 128K context (larger)
Details →
Input price: +150% more expensiveContext window: +300% larger
#5

GPT-5 Mini

OpenAI
same provider; 317% more expensive input; 400K context (larger)
Details →
Input price: +317% more expensiveContext window: +1150% larger
Methodology

How candidates are ranked

Candidates are ranked by how much of the source model's profile each one preserves — weighing switching cost (same provider or model family surface first), capability parity (what you keep versus what you'd lose), context window, and pricing direction. A candidate that is itself deprecated is pushed down the list; one that's already retired is never recommended.

Ranking is purely algorithmic — no editorial weighting, no paid placement. Every value is pulled from each provider's own documentation; click any model name to see the source-linked detail.