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Meta Llama3 2 90b Instruct vs Mistral Pixtral Large 2502
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
Meta Llama3 2 90b Instruct
Context window
128K
128,000 tokens · ~96K words
Model
Mistral Pixtral Large 2502
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.
Same context window size for both models.
Meta Llama3 2 90b Instruct and Mistral Pixtral Large 2502 have identical context windows (128K tokens). Mistral Pixtral Large 2502 is 0% cheaper on input.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Meta Llama3 2 90b Instruct | Mistral Pixtral Large 2502 |
|---|---|---|
| Context window | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Max output tokens | 4,096 tokens (4K) | 4,096 tokens (4K) |
| Speed tier | Balanced | Deep |
| Vision | Yes | No |
| Function calling | Yes | 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 | Meta Llama3 2 90b Instruct in | Meta Llama3 2 90b Instruct out | Mistral Pixtral Large 2502 in | Mistral Pixtral Large 2502 out |
|---|---|---|---|---|
| Aws Bedrock | $2.00/M | $2.00/M | $2.00/M | $6.00/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
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