Compare
Llama 2 70b Chat vs Llama 3 3 Nemotron Super 49b V1 5
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
Llama 3 3 Nemotron Super 49b V1 5
Context window
131K
131,072 tokens · ~98K 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.
Llama 3 3 Nemotron Super 49b V1 5 has about 32× the context window of the other in this pair.
Llama 3 3 Nemotron Super 49b V1 5 has 3100% more context capacity (131K vs 4K tokens). Llama 3 3 Nemotron Super 49b V1 5 is 90% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Llama 3 3 Nemotron Super 49b V1 5. Its 131K context fits entire documents without chunking (vs 4K).
RAG / high-volume retrieval
Use Llama 3 3 Nemotron Super 49b V1 5. Input tokens are 90% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Llama 3 3 Nemotron Super 49b V1 5. Its 131K 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.
| Spec | Llama 2 70b Chat | Llama 3 3 Nemotron Super 49b V1 5 |
|---|---|---|
| Context window | 4,096 tokens (4K) | 131,072 tokens (131K) |
| Max output tokens | 4,096 tokens (4K) | 131,072 tokens (131K) |
| Speed tier | Deep | Balanced |
| Vision | No | No |
| Function calling | No | Yes |
| 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 | Llama 2 70b Chat in | Llama 2 70b Chat out | Llama 3 3 Nemotron Super 49b V1 5 in | Llama 3 3 Nemotron Super 49b V1 5 out |
|---|---|---|---|---|
| Anyscale | $1.00/M | $1.00/M | — | — |
| Deepinfra | — | — | $0.100/M | $0.400/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