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Meta Llama3 2 11b Instruct vs Openai Gpt 4o 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.
Model
Meta Llama3 2 11b Instruct
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 11b Instruct and Openai Gpt 4o Mini have identical context windows (128K tokens).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Meta Llama3 2 11b Instruct | Openai Gpt 4o Mini |
|---|---|---|
| Context window | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Max output tokens | 4,096 tokens (4K) | N/A |
| Speed tier | Fast | Fast |
| Vision | Yes | No |
| Function calling | Yes | No |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | Yes |
| 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 11b Instruct in | Meta Llama3 2 11b Instruct out | Openai Gpt 4o Mini in | Openai Gpt 4o Mini out |
|---|---|---|---|---|
| Aws Bedrock | $0.350/M | $0.350/M | — | — |
| Gradient | — | — | — | — |
Frequently asked questions
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