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Databricks Mixtral 8x7b vs Nous Hermes Llama2 13b
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.
Databricks Mixtral 8x7b and Nous Hermes Llama2 13b have identical context windows (4K tokens). Nous Hermes Llama2 13b is 60% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
RAG / high-volume retrieval
Use Nous Hermes Llama2 13b. Input tokens are 60% cheaper — critical when sending large retrieved contexts.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Databricks Mixtral 8x7b | Nous Hermes Llama2 13b |
|---|---|---|
| Context window | 4,096 tokens (4K) | 4,096 tokens (4K) |
| Max output tokens | 4,096 tokens (4K) | 4,096 tokens (4K) |
| Speed tier | Fast | 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 | Databricks Mixtral 8x7b in | Databricks Mixtral 8x7b out | Nous Hermes Llama2 13b in | Nous Hermes Llama2 13b out |
|---|---|---|---|---|
| Databricks | $0.500/M | $1.00/M | — | — |
| Fireworks | — | — | $0.200/M | $0.200/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