Context Window

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Nvidia Nemotron 3 5 Lightning 30b A3b vs Qwen2p5 0p5b

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 3 5 Lightning 30b A3b

Context window

66K

65,536 tokens · ~49K words

Model page
Alibaba

Model

Qwen2p5 0p5b

Context window

33K

32,768 tokens · ~25K 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 3 5 Lightning 30b A3b66K
Qwen2p5 0p5b33K

Nvidia Nemotron 3 5 Lightning 30b A3b has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Nvidia Nemotron 3 5 Lightning 30b A3b has 100% more context capacity (65K vs 32K tokens). Qwen2p5 0p5b is 33% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Nvidia Nemotron 3 5 Lightning 30b A3b. Its 65K context fits entire documents without chunking (vs 32K).

  • RAG / high-volume retrieval

    Use Qwen2p5 0p5b. Input tokens are 33% 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 3 5 Lightning 30b A3bQwen2p5 0p5b
Context window65,536 tokens (65K)32,768 tokens (32K)
Max output tokensN/A32,768 tokens (32K)
Speed tierFastBalanced
VisionNoNo
Function callingNoNo
Extended thinkingNoNo
Prompt cachingYesNo
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 3 5 Lightning 30b A3b inNvidia Nemotron 3 5 Lightning 30b A3b outQwen2p5 0p5b inQwen2p5 0p5b out
Fireworks——$0.100/M$0.100/M
Gmi$0.150/M$1.00/M——

Frequently asked questions

Nvidia Nemotron 3 5 Lightning 30b A3b has a larger context window: 65K tokens vs 32K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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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.

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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