Context Window

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Codellama 70b Instruct vs Llama V3p2 90b Vision

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

Codellama 70b Instruct

Context window

4K

4,096 tokens · ~3K words

Model page
Meta

Model

Llama V3p2 90b Vision

Image input

Context window

16K

16,384 tokens · ~12K 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.

Codellama 70b Instruct4K
Llama V3p2 90b Vision16K

Llama V3p2 90b Vision has about 4× the context window of the other in this pair.

Token calculator →Memory savings →

Llama V3p2 90b Vision has 300% more context capacity (16K vs 4K tokens). Llama V3p2 90b Vision is 9% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Llama V3p2 90b Vision. Its 16K context fits entire documents without chunking (vs 4K).

  • RAG / high-volume retrieval

    Use Llama V3p2 90b Vision. Input tokens are 9% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Llama V3p2 90b Vision. Its 16K 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.

SpecCodellama 70b InstructLlama V3p2 90b Vision
Context window4,096 tokens (4K)16,384 tokens (16K)
Max output tokens4,096 tokens (4K)16,384 tokens (16K)
Speed tierDeepBalanced
VisionNoYes
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.

ProviderCodellama 70b Instruct inCodellama 70b Instruct outLlama V3p2 90b Vision inLlama V3p2 90b Vision out
Anyscale$1.00/M$1.00/M——
Fireworks——$0.900/M$0.900/M

Frequently asked questions

Llama V3p2 90b Vision has a larger context window: 16K tokens vs 4K. 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