Context Window

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Gpt 3 5 Turbo 0125 vs Qwen VL Plus

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 3 5 Turbo 0125

Tool calling

Context window

16K

16,384 tokens · ~12K words

Model page
Alibaba

Model

Qwen VL Plus

Image input

Context window

8K

8,192 tokens · ~6K 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 3 5 Turbo 012516K
Qwen VL Plus8K

Gpt 3 5 Turbo 0125 has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Gpt 3 5 Turbo 0125 has 100% more context capacity (16K vs 8K tokens). Qwen VL Plus is 58% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Gpt 3 5 Turbo 0125. Its 16K context fits entire documents without chunking (vs 8K).

  • RAG / high-volume retrieval

    Use Qwen VL Plus. Input tokens are 58% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Gpt 3 5 Turbo 0125. Its 4K 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 3 5 Turbo 0125Qwen VL Plus
Context window16,384 tokens (16K)8,192 tokens (8K)
Max output tokens4,096 tokens (4K)2,048 tokens (2K)
Speed tierBalancedBalanced
VisionNoYes
Function callingYesNo
Extended thinkingNoNo
Prompt cachingNoYes
Batch APIYesNo
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 3 5 Turbo 0125 inGpt 3 5 Turbo 0125 outQwen VL Plus inQwen VL Plus out
Azure$0.500/M$1.50/M——
Openai$0.500/M$1.50/M——
Openrouter——$0.210/M$0.630/M

Frequently asked questions

Gpt 3 5 Turbo 0125 has a larger context window: 16K tokens vs 8K. 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