Context Window

Compare

Meta Llama3 70b Instruct vs Phi 3 Small 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.

Meta

Model

Meta Llama3 70b Instruct

Context window

8K

8,192 tokens · ~6K words

Model page
Microsoft

Model

Phi 3 Small 8k

Context window

8K

8,192 tokens · ~6K words

Model page

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.

Meta Llama3 70b Instruct8K
Phi 3 Small 8k8K

Same context window size for both models.

Token calculator →Memory savings →

Meta Llama3 70b Instruct and Phi 3 Small 8k have identical context windows (8K tokens). Phi 3 Small 8k is 95% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Phi 3 Small 8k. Input tokens are 95% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Meta Llama3 70b Instruct. 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.

SpecMeta Llama3 70b InstructPhi 3 Small 8k
Context window8,192 tokens (8K)8,192 tokens (8K)
Max output tokens8,192 tokens (8K)4,096 tokens (4K)
Speed tierDeepBalanced
VisionNoNo
Function callingNoNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AN/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.

ProviderMeta Llama3 70b Instruct inMeta Llama3 70b Instruct outPhi 3 Small 8k inPhi 3 Small 8k out
Aws Bedrock$3.18/M$4.20/M——
Azure——$0.150/M$0.600/M

Frequently asked questions

Phi 3 Small 8k has a larger context window: 8K tokens vs 8K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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.

Calculate your savingsLearn about Mem0

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model