Compare
Gpt 5 2 Chat Latest vs Nemotron 3 Super
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 5 2 Chat Latest
Context window
128K
128,000 tokens · ~96K 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.
Nemotron 3 Super has about 2× the context window of the other in this pair.
Nemotron 3 Super has 104% more context capacity (262K vs 128K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Nemotron 3 Super. Its 262K context fits entire documents without chunking (vs 128K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Gpt 5 2 Chat Latest | Nemotron 3 Super |
|---|---|---|
| Context window | 128,000 tokens (128K) | 262,144 tokens (262K) |
| Max output tokens | 16,384 tokens (16K) | N/A |
| Speed tier | Balanced | Balanced |
| Vision | Yes | No |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | Yes | Yes |
| Batch API | No | No |
| Release date | N/A | Mar 2026 |
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.
| Provider | Gpt 5 2 Chat Latest in | Gpt 5 2 Chat Latest out | Nemotron 3 Super in | Nemotron 3 Super out |
|---|---|---|---|---|
| Openai | $1.75/M | $14.00/M | — | — |
Frequently asked questions
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
80% less to send — works with any model