Context Window

Compare

Moonshot V1 8k 0430 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.

Moonshot

Model

Moonshot V1 8k 0430

Tool calling

Context window

8K

8,192 tokens · ~6K 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.

Moonshot V1 8k 04308K
Qwen VL Plus8K

Same context window size for both models.

Token calculator →Memory savings →

Moonshot V1 8k 0430 and Qwen VL Plus have identical context windows (8K tokens). Moonshot V1 8k 0430 is 4% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Moonshot V1 8k 0430. Input tokens are 4% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Moonshot V1 8k 0430. Its 8K 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.

SpecMoonshot V1 8k 0430Qwen VL Plus
Context window8,192 tokens (8K)8,192 tokens (8K)
Max output tokens8,192 tokens (8K)2,048 tokens (2K)
Speed tierBalancedBalanced
VisionNoYes
Function callingYesNo
Extended thinkingNoNo
Prompt cachingNoYes
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.

ProviderMoonshot V1 8k 0430 inMoonshot V1 8k 0430 outQwen VL Plus inQwen VL Plus out
Moonshot$0.200/M$2.00/M——
Openrouter——$0.210/M$0.630/M

Frequently asked questions

Qwen VL Plus has a larger context window: 8K 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.

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