Context Window

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Nvidia Nemotron Nano 9b vs Qwen2 5 Vl 72b

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.

Nvidia

Model

Nvidia Nemotron Nano 9b

Tool calling

Context window

131K

131,072 tokens · ~98K words

Model page
Alibaba

Model

Qwen2 5 Vl 72b

Image inputTool 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.

Nvidia Nemotron Nano 9b131K
Qwen2 5 Vl 72b131K

Same context window size for both models.

Token calculator →Memory savings →

Nvidia Nemotron Nano 9b and Qwen2 5 Vl 72b have identical context windows (131K tokens). Nvidia Nemotron Nano 9b is 69% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Nvidia Nemotron Nano 9b. Input tokens are 69% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecNvidia Nemotron Nano 9bQwen2 5 Vl 72b
Context window131,072 tokens (131K)131,072 tokens (131K)
Max output tokens131,072 tokens (131K)131,072 tokens (131K)
Speed tierFastDeep
VisionNoYes
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoYes
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.

ProviderNvidia Nemotron Nano 9b inNvidia Nemotron Nano 9b outQwen2 5 Vl 72b inQwen2 5 Vl 72b out
Aws Bedrock$0.060/M$0.230/M——
Deepinfra$0.040/M$0.160/M——
Fireworks$0.200/M$0.200/M——
Nebius——$0.130/M$0.400/M
Novita——$0.800/M$0.800/M
Ovhcloud——$0.910/M$0.910/M

Frequently asked questions

Qwen2 5 Vl 72b 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