Migration assistant

Replacing Amazon Nova Micro?

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.

AB
Migrating from

Amazon Nova Micro

AWS Bedrock · Amazon Nova · Active
Input: $0.04/M Output: $0.14/M Context: 128K
View detail →
#1 RECOMMENDED

Amazon Nova Sonic

AWS Bedrock · Amazon Nova
same provider; same family; 300K context (larger)
View full detail →
What changes if you switch
Field Amazon Nova Micro → Amazon Nova Sonic Impact
Input price $0.04/M → — Candidate price not verified
Output price $0.14/M → — Candidate price not verified
Context window 128K tokens → 300K tokens +134% larger
Function calling ✓ supported → ✓ supported Preserved
Lifecycle Active → Active Same status
Other candidates
#2

Amazon Nova Lite

AWS Bedrock
same provider; same family; 71% more expensive input; 300K context (larger)
Details →
Input price: +71% more expensiveOutput price: +71% more expensiveContext window: +134% larger
#3

Amazon Nova Premier

AWS Bedrock
same provider; same family; 7043% more expensive input; 1M context (larger)
Details →
Input price: +7043% more expensiveOutput price: +8829% more expensiveContext window: +681% larger
#4

Amazon Nova Pro

AWS Bedrock
same provider; same family; 2186% more expensive input; 300K context (larger)
Details →
Input price: +2186% more expensiveOutput price: +2186% more expensiveContext window: +134% larger
#5

Amazon Nova Canvas

AWS Bedrock
same provider; same family; loses 1 capability
Details →
Function calling: LOST — re-evaluate before switching
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.