Context Window

Compare

o3 Mini High vs Qwen3.5-122B-A10B

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

o3 Mini High

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Alibaba

Model

Qwen3.5-122B-A10B

Image inputTool calling

Context window

262K

262,144 tokens · ~197K 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.

o3 Mini High128K
Qwen3.5-122B-A10B262K

Qwen3.5-122B-A10B has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen3.5-122B-A10B has 104% more context capacity (262K vs 128K tokens). Qwen3.5-122B-A10B is 63% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen3.5-122B-A10B. Its 262K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Qwen3.5-122B-A10B. Input tokens are 63% cheaper — critical when sending large retrieved contexts.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

Speco3 Mini HighQwen3.5-122B-A10B
Context window128,000 tokens (128K)262,144 tokens (262K)
Max output tokens65,536 tokens (65K)65,536 tokens (65K)
Speed tierFastBalanced
VisionNoYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesNo
Batch APIYesNo
Release dateFeb 2025Feb 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.

Providero3 Mini High ino3 Mini High outQwen3.5-122B-A10B inQwen3.5-122B-A10B out
Openrouter$1.10/M$4.40/M$0.400/M$2.00/M

Frequently asked questions

Qwen3.5-122B-A10B has a larger context window: 262K 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