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Mistral Large2 vs Phi 3 5 Mini
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.
Mistral Large2 and Phi 3 5 Mini have identical context windows (128K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long output (reports, code files)
Use Mistral Large2. Its 8K 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 | Mistral Large2 | Phi 3 5 Mini |
|---|---|---|
| Context window | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Max output tokens | 8,192 tokens (8K) | 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 | Mistral Large2 in | Mistral Large2 out | Phi 3 5 Mini in | Phi 3 5 Mini out |
|---|---|---|---|---|
| Azure | — | — | $0.130/M | $0.520/M |
| Snowflake | — | — | — | — |
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