Context Window

Compare

Llama 3 3 70b Instruct Fp8 Fast vs Meta Llama 3 1 70b

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

Llama 3 3 70b Instruct Fp8 Fast

Tool calling

Context window

24K

24,000 tokens · ~18K words

Model page
Meta

Model

Meta Llama 3 1 70b

Context window

128K

128,000 tokens · ~96K 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.

Llama 3 3 70b Instruct Fp8 Fast24K
Meta Llama 3 1 70b128K

Meta Llama 3 1 70b has about 5.3× the context window of the other in this pair.

Token calculator →Memory savings →

Meta Llama 3 1 70b has 433% more context capacity (128K vs 24K tokens). Meta Llama 3 1 70b is 59% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Meta Llama 3 1 70b. Its 128K context fits entire documents without chunking (vs 24K).

  • RAG / high-volume retrieval

    Use Meta Llama 3 1 70b. Input tokens are 59% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Llama 3 3 70b Instruct Fp8 Fast. Its 24K 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.

SpecLlama 3 3 70b Instruct Fp8 FastMeta Llama 3 1 70b
Context window24,000 tokens (24K)128,000 tokens (128K)
Max output tokens24,000 tokens (24K)2,048 tokens (2K)
Speed tierDeepDeep
VisionNoNo
Function callingYesNo
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.

ProviderLlama 3 3 70b Instruct Fp8 Fast inLlama 3 3 70b Instruct Fp8 Fast outMeta Llama 3 1 70b inMeta Llama 3 1 70b out
Azure——$2.68/M$3.54/M
Cloudflare$0.293/M$2.25/M——
Deepinfra——$0.400/M$0.400/M
Friendliai——$0.600/M$0.600/M
Hyperbolic——$0.120/M$0.300/M
Nebius——$0.130/M$0.400/M
Ovhcloud——$0.670/M$0.670/M

Frequently asked questions

Meta Llama 3 1 70b has a larger context window: 128K tokens vs 24K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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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.

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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