Compare
Llama 3.1 8B Instruct vs Reka Edge
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
Llama 3.1 8B Instruct
Context window
16K
16,384 tokens · ~12K 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.
Llama 3.1 8B Instruct and Reka Edge have identical context windows (16K tokens).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Llama 3.1 8B Instruct | Reka Edge |
|---|---|---|
| Context window | 16,384 tokens (16K) | 16,384 tokens (16K) |
| Max output tokens | 16,384 tokens (16K) | 16,384 tokens (16K) |
| Speed tier | Fast | Balanced |
| Vision | No | Yes |
| Function calling | Yes | Yes |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | Jul 2024 | Mar 2026 |
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