Context Window

Compare

Deepseek R1 0528 Qwen3 8b vs GPT Audio Mini

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

Deepseek R1 0528 Qwen3 8b

Context window

128K

128,000 tokens · ~96K words

Model page
Openai

Model

GPT Audio Mini

Tool calling

Context window

128K

128,000 tokens · ~96K 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.

Deepseek R1 0528 Qwen3 8b128K
GPT Audio Mini128K

Same context window size for both models.

Token calculator →Memory savings →

Deepseek R1 0528 Qwen3 8b and GPT Audio Mini have identical context windows (128K tokens). Deepseek R1 0528 Qwen3 8b is 90% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Deepseek R1 0528 Qwen3 8b. Input tokens are 90% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Deepseek R1 0528 Qwen3 8b. 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.

SpecDeepseek R1 0528 Qwen3 8bGPT Audio Mini
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens32,000 tokens (32K)16,384 tokens (16K)
Speed tierFastFast
VisionNoNo
Function callingNoYes
Extended thinkingYesNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AJan 2026

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.

ProviderDeepseek R1 0528 Qwen3 8b inDeepseek R1 0528 Qwen3 8b outGPT Audio Mini inGPT Audio Mini out
Novita$0.060/M$0.090/M——
Openai——$0.600/M$2.40/M

Frequently asked questions

GPT Audio Mini has a larger context window: 128K tokens vs 128K. 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