Context Window

Compare

Solar Pro 4 vs Xai Grok 4 3

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.

Upstage

Model

Solar Pro 4

Tool calling

Context window

524K

524,288 tokens · ~393K words

Model page
Xai

Model

Xai Grok 4 3

Image inputTool calling

Context window

131K

131,072 tokens · ~98K 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.

Solar Pro 4524K
Xai Grok 4 3131K

Solar Pro 4 has about 4× the context window of the other in this pair.

Token calculator →Memory savings →

Solar Pro 4 has 300% more context capacity (524K vs 131K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Solar Pro 4. Its 524K context fits entire documents without chunking (vs 131K).

  • Long output (reports, code files)

    Use Solar Pro 4. Its 131K 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.

SpecSolar Pro 4Xai Grok 4 3
Context window524,288 tokens (524K)131,072 tokens (131K)
Max output tokens131,072 tokens (131K)16,384 tokens (16K)
Speed tierBalancedBalanced
VisionNoYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesYes
Batch APINoNo
Release dateAug 2026N/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.

ProviderSolar Pro 4 inSolar Pro 4 outXai Grok 4 3 inXai Grok 4 3 out
Aws Bedrock——$1.25/M$2.50/M

Frequently asked questions

Solar Pro 4 has a larger context window: 524K tokens vs 131K. 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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Use a smaller model.
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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