Context Window

Compare

Deep Research Preview 04 2026 vs Qwen2 5 72b Instruct

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.

Google

Model

Deep Research Preview 04 2026

Image input

Context window

131K

131,072 tokens · ~98K words

Model page
Alibaba

Model

Qwen2 5 72b Instruct

Tool calling

Context window

131K

131,072 tokens · ~98K 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.

Deep Research Preview 04 2026131K
Qwen2 5 72b Instruct131K

Same context window size for both models.

Token calculator →Memory savings →

Deep Research Preview 04 2026 and Qwen2 5 72b Instruct have identical context windows (131K tokens). Qwen2 5 72b Instruct is 40% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Qwen2 5 72b Instruct. Input tokens are 40% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecDeep Research Preview 04 2026Qwen2 5 72b Instruct
Context window131,072 tokens (131K)131,072 tokens (131K)
Max output tokens65,536 tokens (65K)N/A
Speed tierBalancedDeep
VisionYesNo
Function callingNoYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AN/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.

ProviderDeep Research Preview 04 2026 inDeep Research Preview 04 2026 outQwen2 5 72b Instruct inQwen2 5 72b Instruct out
Google$2.00/M$12.00/M——
Together Ai——$1.20/M$1.20/M

Frequently asked questions

Qwen2 5 72b Instruct has a larger context window: 131K tokens vs 131K. 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