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Llama 2 13b Chat vs Meta Llama 3 1 70b
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.
Meta Llama 3 1 70b has about 31.3× the context window of the other in this pair.
Meta Llama 3 1 70b has 3025% more context capacity (128K vs 4K tokens). Meta Llama 3 1 70b is 52% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Meta Llama 3 1 70b. Its 128K context fits entire documents without chunking (vs 4K).
RAG / high-volume retrieval
Use Meta Llama 3 1 70b. Input tokens are 52% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Llama 2 13b Chat. Its 4K 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 13b Chat | Meta Llama 3 1 70b |
|---|---|---|
| Context window | 4,096 tokens (4K) | 128,000 tokens (128K) |
| Max output tokens | 4,096 tokens (4K) | 2,048 tokens (2K) |
| Speed tier | Fast | Deep |
| 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 | Llama 2 13b Chat in | Llama 2 13b Chat out | Meta Llama 3 1 70b in | Meta Llama 3 1 70b out |
|---|---|---|---|---|
| Anyscale | $0.250/M | $0.250/M | — | — |
| Azure | — | — | $2.68/M | $3.54/M |
| Deepinfra | — | — | $0.400/M | $0.400/M |
| Friendliai | — | — | $0.600/M | $0.600/M |
| Hyperbolic | — | — | $0.120/M | $0.300/M |
| Nebius | — | — | $0.130/M | $0.400/M |
| Ovhcloud | — | — | $0.670/M | $0.670/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