Model Comparison

DeepSeek-V3.2-Exp vs MiniMax M2

Both models are evenly matched across the benchmarks. DeepSeek-V3.2-Exp is 1.7x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

10 benchmarks

DeepSeek-V3.2-Exp outperforms in 5 benchmarks (AIME 2025, GPQA, Humanity's Last Exam, MMLU-Pro, SWE-bench Multilingual), while MiniMax M2 is better at 5 benchmarks (BrowseComp, BrowseComp-zh, LiveCodeBench, SWE-Bench Verified, Terminal-Bench).

Both models are evenly matched across the benchmarks.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2-Exp costs less

For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 1.1x cheaper than MiniMax M2 ($0.30/1M tokens).

For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 2.9x cheaper than MiniMax M2 ($1.20/1M tokens).

In conclusion, MiniMax M2 is more expensive than DeepSeek-V3.2-Exp.*

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
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-Exp has 455.0B more parameters than MiniMax M2, making it 197.8% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
MiniMax
MiniMax M2
230.0Bparameters
685.0B
DeepSeek-V3.2-Exp
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-Exp's 163,840 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
MiniMax
MiniMax M2
Input1,000,000 tokens
Output1,000,000 tokens
Wed Apr 15 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-Exp

MIT

Open weights

MiniMax M2

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while MiniMax M2 was released on 2025-10-27.

MiniMax M2 is 1 month newer than DeepSeek-V3.2-Exp.

DeepSeek-V3.2-Exp

Sep 29, 2025

6 months ago

MiniMax M2

Oct 27, 2025

5 months ago

4w newer

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-Exp is available from Novita. MiniMax M2 is available from MiniMax, Novita.

DeepSeek-V3.2-Exp

novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $0.41/1M

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
Higher AIME 2025 score (89.3% vs 78.0%)
Higher GPQA score (79.9% vs 78.0%)
Higher Humanity's Last Exam score (19.8% vs 12.5%)
Higher MMLU-Pro score (85.0% vs 82.0%)
Higher SWE-bench Multilingual score (57.9% vs 56.5%)
MiniMax
Larger context window (1,000,000 tokens)
Higher BrowseComp score (44.0% vs 40.1%)
Higher BrowseComp-zh score (48.5% vs 47.9%)
Higher LiveCodeBench score (83.0% vs 74.1%)
Higher SWE-Bench Verified score (69.4% vs 67.8%)
Higher Terminal-Bench score (46.3% vs 37.7%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
MiniMax
MiniMax M2

FAQ

Common questions about DeepSeek-V3.2-Exp vs MiniMax M2

Both models are evenly matched across the benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and MiniMax M2 is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. MiniMax M2 scores Tau2 Telecom: 87.0%, LiveCodeBench: 83.0%, MMLU-Pro: 82.0%, AIME 2025: 78.0%, GPQA: 78.0%.
DeepSeek-V3.2-Exp is 1.1x cheaper for input tokens. DeepSeek-V3.2-Exp costs $0.27/M input and $0.41/M output via novita. MiniMax M2 costs $0.30/M input and $1.20/M output via minimax.
DeepSeek-V3.2-Exp supports 164K tokens and MiniMax M2 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (164K vs 1.0M), input pricing ($0.27 vs $0.30/M). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Exp is developed by DeepSeek and MiniMax M2 is developed by MiniMax.