Context Window

Compare

Qwen3 VL 32B Instruct vs ReMM SLERP 13B

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.

Alibaba

Model

Qwen3 VL 32B Instruct

Image inputTool calling

Context window

131K

131,072 tokens · ~98K words

Model page
Undi95

Model

ReMM SLERP 13B

Context window

6K

6,144 tokens · ~5K 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.

Qwen3 VL 32B Instruct131K
ReMM SLERP 13B6K

Qwen3 VL 32B Instruct has about 21.3× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen3 VL 32B Instruct has 2033% more context capacity (131K vs 6K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen3 VL 32B Instruct. Its 131K context fits entire documents without chunking (vs 6K).

  • Long output (reports, code files)

    Use Qwen3 VL 32B 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.

SpecQwen3 VL 32B InstructReMM SLERP 13B
Context window131,072 tokens (131K)6,144 tokens (6K)
Max output tokens32,768 tokens (32K)4,096 tokens (4K)
Speed tierBalancedFast
VisionYesNo
Function callingYesNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateOct 2025Jul 2023

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.

ProviderQwen3 VL 32B Instruct inQwen3 VL 32B Instruct outReMM SLERP 13B inReMM SLERP 13B out
Openrouter——$1.88/M$1.88/M

Frequently asked questions

Qwen3 VL 32B Instruct has a larger context window: 131K tokens vs 6K. 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