Model Comparison

Gemini 3.5 Flash-Lite vs MiniMax M2Which is better in 2026?

Comparing Gemini 3.5 Flash-Lite and MiniMax M2 across benchmarks, pricing, and capabilities.

Verdict: Gemini 3.5 Flash-Lite vs MiniMax M2 — which is better?

Gemini 3.5 Flash-Lite (by Google) and MiniMax M2 (by MiniMax) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

On price, MiniMax M2 is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 3.5 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemini 3.5 Flash-Lite if…

  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Jul 2026

Choose MiniMax M2 if…

  • cost matters — it's about 1.6x cheaper per token
  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemini 3.5 Flash-Lite and MiniMax M2don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

MiniMax M2 costs less

For input processing, Gemini 3.5 Flash-Lite ($0.30/1M tokens) costs the same as MiniMax M2 ($0.30/1M tokens).

For output processing, Gemini 3.5 Flash-Lite ($2.50/1M tokens) is 2.1x more expensive than MiniMax M2 ($1.20/1M tokens).

In conclusion, Gemini 3.5 Flash-Lite is more expensive than MiniMax M2.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Jul 25 2026 • llm-stats.com
Google
Gemini 3.5 Flash-Lite
Input tokens$0.30
Output tokens$2.50
Best providerGoogle
MiniMax
MiniMax M2
Input tokens$0.30
Output tokens$1.20
Best providerMiniMax
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 3.5 Flash-Lite accepts 1,048,576 input tokens compared to MiniMax M2's 1,000,000 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while Gemini 3.5 Flash-Lite is limited to 65,536 tokens.

Google
Gemini 3.5 Flash-Lite
Input1,048,576 tokens
Output65,536 tokens
MiniMax
MiniMax M2
Input1,000,000 tokens
Output1,000,000 tokens
Sat Jul 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 3.5 Flash-Lite supports multimodal inputs, whereas MiniMax M2 does not.

Gemini 3.5 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 3.5 Flash-Lite

Text
Images
Audio
Video

MiniMax M2

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3.5 Flash-Lite is licensed under a proprietary license, while MiniMax M2 uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 3.5 Flash-Lite

Proprietary

Closed source

MiniMax M2

MIT

Open weights

Release Timeline

When each model was launched

Gemini 3.5 Flash-Lite was released on 2026-07-21, while MiniMax M2 was released on 2025-10-27.

Gemini 3.5 Flash-Lite is 9 months newer than MiniMax M2.

Gemini 3.5 Flash-Lite

Jul 21, 2026

3 days ago

8mo newer
MiniMax M2

Oct 27, 2025

9 months ago

Knowledge Cutoff

When training data ends

Gemini 3.5 Flash-Lite has a documented knowledge cutoff of 2026-03-31, while MiniMax M2's cutoff date is not specified.

We can confirm Gemini 3.5 Flash-Lite's training data extends to 2026-03-31, but cannot make a direct comparison without MiniMax M2's cutoff date.

Gemini 3.5 Flash-Lite

Mar 2026

MiniMax M2

—

Provider Availability

Gemini 3.5 Flash-Lite is available from Google. MiniMax M2 is available from MiniMax, Novita.

Gemini 3.5 Flash-Lite

google logo
Google
Input Price:Input: $0.30/1MOutput Price:Output: $2.50/1M

MiniMax M2

minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
MiniMax
Less expensive output tokens
Has open weights

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemini 3.5 Flash-Lite and MiniMax M2 side-by-side, then vote on the output you prefer.

Gemini 3.5 Flash-Lite
✓ Preferred
MiniMax M2
Open in Playground
AI Model Comparison Table
Feature
Google
Gemini 3.5 Flash-Lite
MiniMax
MiniMax M2

FAQ

Common questions about Gemini 3.5 Flash-Lite vs MiniMax M2.

Which is better, Gemini 3.5 Flash-Lite or MiniMax M2?

Gemini 3.5 Flash-Lite (Google) and MiniMax M2 (MiniMax) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemini 3.5 Flash-Lite compare to MiniMax M2 in benchmarks?

Gemini 3.5 Flash-Lite scores CharXiv-R: 76.5%, OSWorld-Verified: 74.0%, SWE-Bench Pro: 54.2%, Terminal-Bench 2.1: 54.0%, MLE-Bench: 39.2%. MiniMax M2 scores Tau2 Telecom: 87.0%, LiveCodeBench: 83.0%, MMLU-Pro: 82.0%, AIME 2025: 78.0%, GPQA: 78.0%.

Is Gemini 3.5 Flash-Lite cheaper than MiniMax M2?

Both models cost $0.30 per million input tokens.

What are the context window sizes for Gemini 3.5 Flash-Lite and MiniMax M2?

Gemini 3.5 Flash-Lite supports 1.0M tokens and MiniMax M2 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 3.5 Flash-Lite and MiniMax M2?

Key differences include context window (1.0M vs 1.0M), multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 3.5 Flash-Lite and MiniMax M2?

Gemini 3.5 Flash-Lite is developed by Google and MiniMax M2 is developed by MiniMax.

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