Context Window

Compare

Llama 3 1 405b vs o4 Mini High

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 405b

Context window

4K

4,096 tokens · ~3K words

Model page
Openai

Model

o4 Mini High

Image inputTool calling

Context window

200K

200,000 tokens · ~150K 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 405b4K
o4 Mini High200K

o4 Mini High has about 48.8× the context window of the other in this pair.

Token calculator →Memory savings →

o4 Mini High has 4782% more context capacity (200K vs 4K tokens). o4 Mini High is 68% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use o4 Mini High. Its 200K context fits entire documents without chunking (vs 4K).

  • RAG / high-volume retrieval

    Use o4 Mini High. Input tokens are 68% 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 405bo4 Mini High
Context window4,096 tokens (4K)200,000 tokens (200K)
Max output tokensN/A100,000 tokens (100K)
Speed tierDeepFast
VisionNoYes
Function callingNoYes
Extended thinkingNoYes
Prompt cachingNoYes
Batch APINoNo
Release dateN/AApr 2025

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 405b inLlama 3 1 405b outo4 Mini High ino4 Mini High out
Openrouter——$1.10/M$4.40/M
Together Ai$3.50/M$3.50/M——

Frequently asked questions

o4 Mini High has a larger context window: 200K 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.

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