Context Window

Compare

Gpt Realtime 1 5 vs Qwen2.5 VL 72B Instruct

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 Realtime 1 5

Tool calling

Context window

32K

32,000 tokens · ~24K words

Model page
Alibaba

Model

Qwen2.5 VL 72B Instruct

Image input

Context window

33K

32,768 tokens · ~25K 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 Realtime 1 532K
Qwen2.5 VL 72B Instruct33K

Qwen2.5 VL 72B Instruct has about 1× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen2.5 VL 72B Instruct has 2% more context capacity (32K vs 32K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen2.5 VL 72B Instruct. Its 32K context fits entire documents without chunking (vs 32K).

  • Long output (reports, code files)

    Use Qwen2.5 VL 72B Instruct. Its 32K 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 Realtime 1 5Qwen2.5 VL 72B Instruct
Context window32,000 tokens (32K)32,768 tokens (32K)
Max output tokens4,096 tokens (4K)32,768 tokens (32K)
Speed tierBalancedDeep
VisionNoYes
Function callingYesNo
Extended thinkingNoNo
Prompt cachingYesNo
Batch APINoNo
Release dateN/AFeb 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.

ProviderGpt Realtime 1 5 inGpt Realtime 1 5 outQwen2.5 VL 72B Instruct inQwen2.5 VL 72B Instruct out
Openai$4.00/M$16.00/M——

Frequently asked questions

Qwen2.5 VL 72B Instruct has a larger context window: 32K tokens vs 32K. 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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