Context Window

Compare

Gpt 5 2 Chat Latest vs Llama 3 2 11b 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.

Openai

Model

Gpt 5 2 Chat Latest

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Meta

Model

Llama 3 2 11b Vision

Image inputTool calling

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.

Gpt 5 2 Chat Latest128K
Llama 3 2 11b Vision128K

Same context window size for both models.

Token calculator →Memory savings →

Gpt 5 2 Chat Latest and Llama 3 2 11b Vision have identical context windows (128K tokens). Llama 3 2 11b Vision is 97% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Llama 3 2 11b Vision. Input tokens are 97% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Gpt 5 2 Chat Latest. 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.

SpecGpt 5 2 Chat LatestLlama 3 2 11b Vision
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens16,384 tokens (16K)2,048 tokens (2K)
Speed tierBalancedFast
VisionYesYes
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesNo
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.

ProviderGpt 5 2 Chat Latest inGpt 5 2 Chat Latest outLlama 3 2 11b Vision inLlama 3 2 11b Vision out
Azure——$0.370/M$0.370/M
Deepinfra——$0.049/M$0.049/M
Ibm Watsonx——$0.350/M$0.350/M
Openai$1.75/M$14.00/M——

Frequently asked questions

Llama 3 2 11b Vision has a larger context window: 128K 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.

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