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MiniMax M2 vs Nvidia Nemotron 3 5 Lightning 30b A3b

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.

Minimax

Model

MiniMax M2

Tool calling

Context window

200K

200,000 tokens · ~150K words

Model page
Nvidia

Model

Nvidia Nemotron 3 5 Lightning 30b A3b

Context window

66K

65,536 tokens · ~49K 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.

MiniMax M2200K
Nvidia Nemotron 3 5 Lightning 30b A3b66K

MiniMax M2 has about 3.1× the context window of the other in this pair.

MiniMax M2 has 205% more context capacity (200K vs 65K tokens). Nvidia Nemotron 3 5 Lightning 30b A3b is 50% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use MiniMax M2. Its 200K context fits entire documents without chunking (vs 65K).

  • RAG / high-volume retrieval

    Use Nvidia Nemotron 3 5 Lightning 30b A3b. Input tokens are 50% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecMiniMax M2Nvidia Nemotron 3 5 Lightning 30b A3b
Context window200,000 tokens (200K)65,536 tokens (65K)
Max output tokens8,192 tokens (8K)N/A
Speed tierFastFast
VisionNoNo
Function callingYesNo
Extended thinkingYesNo
Prompt cachingYesYes
Batch APINoNo
Release dateOct 2025N/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.

ProviderMiniMax M2 inMiniMax M2 outNvidia Nemotron 3 5 Lightning 30b A3b inNvidia Nemotron 3 5 Lightning 30b A3b out
Fireworks$0.300/M$1.20/M——
Gmi$0.300/M$1.20/M$0.150/M$1.00/M
Minimax$0.300/M$1.20/M——
Novita$0.300/M$1.20/M——
Openrouter$0.300/M$1.20/M——

Frequently asked questions

MiniMax M2 has a larger context window: 200K tokens vs 65K. 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.

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