Context Window

Compare

Amazon Nova Lite vs Apac Amazon Nova Lite

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Amazon

Model

Amazon Nova Lite

Image inputTool calling

Context window

300K

300,000 tokens · ~225K words

Model page
Amazon

Model

Apac Amazon Nova Lite

Image inputTool calling

Context window

300K

300,000 tokens · ~225K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

Amazon Nova Lite300K
Apac Amazon Nova Lite300K

Same context window size for both models.

Token calculator →Memory savings →

Amazon Nova Lite and Apac Amazon Nova Lite have identical context windows (300K tokens). Amazon Nova Lite is 4% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Amazon Nova Lite. Input tokens are 4% cheaper — critical when sending large retrieved contexts.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecAmazon Nova LiteApac Amazon Nova Lite
Context window300,000 tokens (300K)300,000 tokens (300K)
Max output tokens10,000 tokens (10K)10,000 tokens (10K)
Speed tierBalancedBalanced
VisionYesYes
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AN/A

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderAmazon Nova Lite inAmazon Nova Lite outApac Amazon Nova Lite inApac Amazon Nova Lite out
Aws Bedrock$0.060/M$0.240/M$0.063/M$0.252/M

Frequently asked questions

Apac Amazon Nova Lite has a larger context window: 300K tokens vs 300K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Calculate your savingsLearn about Mem0

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model