Context Window

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Claude Opus 4.7 (Fast) vs Qwen Plus 2025 07 14

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.

Anthropic

Model

Claude Opus 4.7 (Fast)

Image inputTool calling

Context window

1M

1,000,000 tokens · ~750K words

Model page
Alibaba

Model

Qwen Plus 2025 07 14

Tool calling

Context window

129K

129,024 tokens · ~97K 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.

Claude Opus 4.7 (Fast)1M
Qwen Plus 2025 07 14129K

Claude Opus 4.7 (Fast) has about 7.8× the context window of the other in this pair.

Token calculator →Memory savings →

Claude Opus 4.7 (Fast) has 675% more context capacity (1000K vs 129K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Claude Opus 4.7 (Fast). Its 1000K context fits entire documents without chunking (vs 129K).

  • Long output (reports, code files)

    Use Claude Opus 4.7 (Fast). Its 128K 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.

SpecClaude Opus 4.7 (Fast)Qwen Plus 2025 07 14
Context window1,000,000 tokens (1000K)129,024 tokens (129K)
Max output tokens128,000 tokens (128K)16,384 tokens (16K)
Speed tierDeepBalanced
VisionYesNo
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesNo
Batch APIYesNo
Release dateMay 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.

ProviderClaude Opus 4.7 (Fast) inClaude Opus 4.7 (Fast) outQwen Plus 2025 07 14 inQwen Plus 2025 07 14 out
Alibaba Cloud——$0.400/M$1.20/M

Frequently asked questions

Claude Opus 4.7 (Fast) has a larger context window: 1000K tokens vs 129K. 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.
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