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Amazon Nova Micro vs Ft:gpt 4 1 2025 04 14

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 Micro

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Openai

Model

Ft:gpt 4 1 2025 04 14

Tool calling

Context window

1.0M

1,047,576 tokens · ~786K 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 Micro128K
Ft:gpt 4 1 2025 04 141.0M

Ft:gpt 4 1 2025 04 14 has about 8.2× the context window of the other in this pair.

Ft:gpt 4 1 2025 04 14 has 718% more context capacity (1047K vs 128K tokens). Amazon Nova Micro is 98% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Ft:gpt 4 1 2025 04 14. Its 1047K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Amazon Nova Micro. Input tokens are 98% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Ft:gpt 4 1 2025 04 14. Its 32K max output lets you generate complete artifacts in one request.

Full specs

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

SpecAmazon Nova MicroFt:gpt 4 1 2025 04 14
Context window128,000 tokens (128K)1,047,576 tokens (1047K)
Max output tokens10,000 tokens (10K)32,768 tokens (32K)
Speed tierBalancedBalanced
VisionNoNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoYes
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 Micro inAmazon Nova Micro outFt:gpt 4 1 2025 04 14 inFt:gpt 4 1 2025 04 14 out
Aws Bedrock$0.035/M$0.140/M
Openai$3.00/M$12.00/M

Frequently asked questions

Ft:gpt 4 1 2025 04 14 has a larger context window: 1047K tokens vs 128K. 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.

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