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Meta Textgeneration Llama 2 70b vs Nemotron Nano V2 12b Vl
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.
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.
Same context window size for both models.
Meta Textgeneration Llama 2 70b and Nemotron Nano V2 12b Vl have identical context windows (4K tokens).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Meta Textgeneration Llama 2 70b | Nemotron Nano V2 12b Vl |
|---|---|---|
| Context window | 4,096 tokens (4K) | 4,096 tokens (4K) |
| Max output tokens | 4,096 tokens (4K) | 4,096 tokens (4K) |
| Speed tier | Deep | Fast |
| Vision | No | No |
| Function calling | No | No |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | N/A | N/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.
| Provider | Meta Textgeneration Llama 2 70b in | Meta Textgeneration Llama 2 70b out | Nemotron Nano V2 12b Vl in | Nemotron Nano V2 12b Vl out |
|---|---|---|---|---|
| Aws Sagemaker | — | — | — | — |
| Fireworks | — | — | $0.100/M | $0.100/M |
Frequently asked questions
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Use a smaller model.
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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