Model Comparison

DeepSeek VL2 vs MiniMax M2Which is better in 2026?

Comparing DeepSeek VL2 and MiniMax M2 across benchmarks, pricing, and capabilities.

Verdict: DeepSeek VL2 vs MiniMax M2 — which is better?

DeepSeek VL2 (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.

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 VL2 if…

  • you are already invested in the DeepSeek ecosystem

Choose MiniMax M2 if…

  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped Oct 2025

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 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

Model Size

Parameter count comparison

203.0B diff

MiniMax M2 has 203.0B more parameters than DeepSeek VL2, making it 751.9% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
MiniMax
MiniMax M2
230.0Bparameters
27.0B
DeepSeek VL2
230.0B
MiniMax M2

Context Window

Maximum input and output token capacity

MiniMax M2 accepts 1,000,000 input tokens compared to DeepSeek VL2's 129,280 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
MiniMax
MiniMax M2
Input1,000,000 tokens
Output1,000,000 tokens
Mon Jul 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas MiniMax M2 does not.

DeepSeek VL2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2

Text
Images
Audio
Video

MiniMax M2

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while MiniMax M2 uses MIT.

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

DeepSeek VL2

deepseek

Open weights

MiniMax M2

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while MiniMax M2 was released on 2025-10-27.

MiniMax M2 is 11 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.6 years ago

MiniMax M2

Oct 27, 2025

9 months ago

10mo 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 VL2 is available from Replicate. MiniMax M2 is available from MiniMax, Novita.

DeepSeek VL2

replicate logo
Replicate

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

Supports multimodal inputs
Larger context window (1,000,000 tokens)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek VL2 and MiniMax M2 side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
MiniMax M2
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
MiniMax
MiniMax M2

FAQ

Common questions about DeepSeek VL2 vs MiniMax M2.

Which is better, DeepSeek VL2 or MiniMax M2?

DeepSeek VL2 (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 VL2 compare to MiniMax M2 in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. MiniMax M2 scores Tau2 Telecom: 87.0%, LiveCodeBench: 83.0%, MMLU-Pro: 82.0%, AIME 2025: 78.0%, GPQA: 78.0%.

What are the context window sizes for DeepSeek VL2 and MiniMax M2?

DeepSeek VL2 supports 129K 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 VL2 and MiniMax M2?

Key differences include context window (129K vs 1.0M), multimodal support (yes vs no), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and MiniMax M2?

DeepSeek VL2 is developed by DeepSeek and MiniMax M2 is developed by MiniMax.