Compare
GPT-4.1 Nano (batch) vs Nemotron 3 Nano 30B A3B (free)
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.
Model
GPT-4.1 Nano (batch)
Context window
1.0M
1,047,576 tokens · ~786K words
Model
Nemotron 3 Nano 30B A3B (free)
Context window
256K
256,000 tokens · ~192K words
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.
GPT-4.1 Nano (batch) has about 4.1× the context window of the other in this pair.
GPT-4.1 Nano (batch) has 309% more context capacity (1047K vs 256K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use GPT-4.1 Nano (batch). Its 1047K context fits entire documents without chunking (vs 256K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | GPT-4.1 Nano (batch) | Nemotron 3 Nano 30B A3B (free) |
|---|---|---|
| Context window | 1,047,576 tokens (1047K) | 256,000 tokens (256K) |
| Max output tokens | 32,768 tokens (32K) | N/A |
| Speed tier | Fast | Fast |
| Vision | Yes | No |
| Function calling | Yes | Yes |
| Extended thinking | No | Yes |
| Prompt caching | Yes | No |
| Batch API | No | No |
| Release date | Apr 2025 | Dec 2025 |
Frequently asked questions
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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
80% less to send — works with any model