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DeepSeek VL2 vs MiMo-V2.6-Pro

MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 2.9.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 2.9, ranking #19 overall.

MiMo-V2.6-Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek VL2

  • you are already invested in the DeepSeek ecosystem

Choose MiMo-V2.6-Pro

  • overall performance matters — it scores 49.8 and ranks #19 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek VL2
DeepSeek
MiMo-V2.6-Pro
Xiaomi
Core performance indexes
LLM Stats Score
2.9
#314
49.8
#19
Reasoning
-1.9
#332
45.2
#30
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.43 / M
Output price
— / M
$0.87 / M
Context window
129,280
1,048,576

Individual benchmarks

14 reported for DeepSeek VL2 · 18 for MiMo-V2.6-Pro

No common benchmarks found

DeepSeek VL2 and MiMo-V2.6-Prodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

993.0B diff

MiMo-V2.6-Pro has 993.0B more parameters than DeepSeek VL2, making it 3677.8% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Xiaomi
MiMo-V2.6-Pro
1.0Tparameters
27.0B
DeepSeek VL2
1020.0B
MiMo-V2.6-Pro

Context Window

Maximum input and output token capacity

MiMo-V2.6-Pro accepts 1,048,576 input tokens compared to DeepSeek VL2's 129,280 tokens. Only DeepSeek VL2 specifies output context (129,280 tokens).

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Xiaomi
MiMo-V2.6-Pro
Input1,048,576 tokens
Output- tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek VL2 and MiMo-V2.6-Pro support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek VL2

Text
Images
Audio
Video

MiMo-V2.6-Pro

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while MiMo-V2.6-Pro uses MIT.

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

DeepSeek VL2

deepseek

Open weights

MiMo-V2.6-Pro

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while MiMo-V2.6-Pro was released on 2026-09-22.

MiMo-V2.6-Pro is 22 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.8 years ago

MiMo-V2.6-Pro

Sep 22, 2026

-1 days ago

1.8yr 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. MiMo-V2.6-Pro is available from Xiaomi.

DeepSeek VL2

replicate logo
Replicate

MiMo-V2.6-Pro

xiaomi logo
Xiaomi
Input Price:Input: $0.43/1MOutput Price:Output: $0.87/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek VL2 and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
MiMo-V2.6-Pro
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs MiMo-V2.6-Pro.

Which is better, DeepSeek VL2 or MiMo-V2.6-Pro?

MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 2.9. DeepSeek VL2 is made by DeepSeek and MiMo-V2.6-Pro is made by Xiaomi. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek VL2 compare to MiMo-V2.6-Pro in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. MiMo-V2.6-Pro scores CyberGym: 94.0%, Terminal-Bench 2.1: 89.9%, OSWorld-Verified: 82.0%, MiMo Cyber Bench: 81.7%, Toolathlon-Verified: 76.9%.

What are the context window sizes for DeepSeek VL2 and MiMo-V2.6-Pro?

DeepSeek VL2 supports 129K tokens and MiMo-V2.6-Pro 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 MiMo-V2.6-Pro?

Key differences include LLM Stats Score (2.9 vs 49.8), context window (129K vs 1.0M), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and MiMo-V2.6-Pro?

DeepSeek VL2 is developed by DeepSeek and MiMo-V2.6-Pro is developed by Xiaomi.

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