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Meta Llama3 8b Instruct vs Moonshot V1 8k
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.
Meta Llama3 8b Instruct and Moonshot V1 8k have identical context windows (8K tokens). Moonshot V1 8k is 44% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
RAG / high-volume retrieval
Use Moonshot V1 8k. Input tokens are 44% 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 | Meta Llama3 8b Instruct | Moonshot V1 8k |
|---|---|---|
| Context window | 8,192 tokens (8K) | 8,192 tokens (8K) |
| Max output tokens | 8,192 tokens (8K) | 8,192 tokens (8K) |
| Speed tier | Fast | Balanced |
| Vision | No | No |
| Function calling | No | 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 8b Instruct in | Meta Llama3 8b Instruct out | Moonshot V1 8k in | Moonshot V1 8k out |
|---|---|---|---|---|
| Aws Bedrock | $0.360/M | $0.720/M | — | — |
| Moonshot | — | — | $0.200/M | $2.00/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