Model Comparison

DeepSeek-V3.2 (Non-thinking) vs MiniMax M2Which is better in 2026?

Comparing DeepSeek-V3.2 (Non-thinking) and MiniMax M2 across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V3.2 (Non-thinking) vs MiniMax M2 — which is better?

DeepSeek-V3.2 (Non-thinking) (by DeepSeek) 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, DeepSeek-V3.2 (Non-thinking) is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

MiniMax M2 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek-V3.2 (Non-thinking) if…

  • cost matters — it's about 1.7x cheaper per token
  • you want the most recent training data — it shipped Dec 2025

Choose MiniMax M2 if…

  • you process long inputs — it offers a 1,000,000 token context window
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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2 (Non-thinking) 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

DeepSeek-V3.2 (Non-thinking) costs less

For input processing, DeepSeek-V3.2 (Non-thinking) ($0.28/1M tokens) is 1.1x cheaper than MiniMax M2 ($0.30/1M tokens).

For output processing, DeepSeek-V3.2 (Non-thinking) ($0.42/1M tokens) is 2.9x cheaper than MiniMax M2 ($1.20/1M tokens).

In conclusion, MiniMax M2 is more expensive than DeepSeek-V3.2 (Non-thinking).*

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

Lowest available price from all providers
Sat Jun 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
MiniMax
MiniMax M2
Input tokens$0.30
Output tokens$1.20
Best providerMiniMax
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

455.0B diff

DeepSeek-V3.2 (Non-thinking) has 455.0B more parameters than MiniMax M2, making it 197.8% larger.

DeepSeek
DeepSeek-V3.2 (Non-thinking)
685.0Bparameters
MiniMax
MiniMax M2
230.0Bparameters
685.0B
DeepSeek-V3.2 (Non-thinking)
230.0B
MiniMax M2

Context Window

Maximum input and output token capacity

MiniMax M2 accepts 1,000,000 input tokens compared to DeepSeek-V3.2 (Non-thinking)'s 131,072 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while DeepSeek-V3.2 (Non-thinking) is limited to 8,192 tokens.

DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input131,072 tokens
Output8,192 tokens
MiniMax
MiniMax M2
Input1,000,000 tokens
Output1,000,000 tokens
Sat Jun 13 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V3.2 (Non-thinking)

MIT

Open weights

MiniMax M2

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while MiniMax M2 was released on 2025-10-27.

DeepSeek-V3.2 (Non-thinking) is 1 month newer than MiniMax M2.

DeepSeek-V3.2 (Non-thinking)

Dec 1, 2025

6 months ago

1mo newer
MiniMax M2

Oct 27, 2025

7 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V3.2 (Non-thinking) is available from DeepSeek. MiniMax M2 is available from MiniMax, Novita.

DeepSeek-V3.2 (Non-thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

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

DeepSeek
Less expensive input tokens
Less expensive output tokens
MiniMax
Larger context window (1,000,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Non-thinking)
MiniMax
MiniMax M2

FAQ

Common questions about DeepSeek-V3.2 (Non-thinking) vs MiniMax M2.

Which is better, DeepSeek-V3.2 (Non-thinking) or MiniMax M2?

DeepSeek-V3.2 (Non-thinking) (DeepSeek) 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 DeepSeek-V3.2 (Non-thinking) compare to MiniMax M2 in benchmarks?

MiniMax M2 scores Tau2 Telecom: 87.0%, LiveCodeBench: 83.0%, MMLU-Pro: 82.0%, AIME 2025: 78.0%, GPQA: 78.0%.

Is DeepSeek-V3.2 (Non-thinking) cheaper than MiniMax M2?

DeepSeek-V3.2 (Non-thinking) is 1.1x cheaper for input tokens. DeepSeek-V3.2 (Non-thinking) costs $0.28/M input and $0.42/M output via deepseek. MiniMax M2 costs $0.30/M input and $1.20/M output via minimax.

What are the context window sizes for DeepSeek-V3.2 (Non-thinking) and MiniMax M2?

DeepSeek-V3.2 (Non-thinking) supports 131K 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 DeepSeek-V3.2 (Non-thinking) and MiniMax M2?

Key differences include context window (131K vs 1.0M), input pricing ($0.28 vs $0.30/M). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Non-thinking) and MiniMax M2?

DeepSeek-V3.2 (Non-thinking) is developed by DeepSeek and MiniMax M2 is developed by MiniMax.

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