Context Window

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Llama 3 1 8b Instant vs Nvidia Nemotron Nano 3 30b

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 1 8b Instant

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Nvidia

Model

Nvidia Nemotron Nano 3 30b

Tool calling

Context window

262K

262,144 tokens · ~197K 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 1 8b Instant128K
Nvidia Nemotron Nano 3 30b262K

Nvidia Nemotron Nano 3 30b has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Nvidia Nemotron Nano 3 30b has 104% more context capacity (262K vs 128K tokens). Llama 3 1 8b Instant is 16% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Nvidia Nemotron Nano 3 30b. Its 262K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Llama 3 1 8b Instant. Input tokens are 16% cheaper — critical when sending large retrieved contexts.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecLlama 3 1 8b InstantNvidia Nemotron Nano 3 30b
Context window128,000 tokens (128K)262,144 tokens (262K)
Max output tokens8,192 tokens (8K)8,192 tokens (8K)
Speed tierFastFast
VisionNoNo
Function callingYesYes
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 1 8b Instant inLlama 3 1 8b Instant outNvidia Nemotron Nano 3 30b inNvidia Nemotron Nano 3 30b out
Aws Bedrock——$0.060/M$0.240/M
Groq$0.050/M$0.080/M——

Frequently asked questions

Nvidia Nemotron Nano 3 30b has a larger context window: 262K tokens vs 128K. 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