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DeepSeek R1 Distill Qwen 14B vs MiMo-V2.6-Pro

MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 10.9.

DeepSeek · Xiaomi · Updated for 2026

Which is better?

MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 10.9, ranking #19 overall.

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

Choose DeepSeek R1 Distill Qwen 14B

  • 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 and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek R1 Distill Qwen 14B
DeepSeek
MiMo-V2.6-Pro
Xiaomi
Core performance indexes
LLM Stats Score
10.9
#263
49.8
#19
Reasoning
11.3
#259
45.2
#30
Coding
5.5
#201
41.8
#9
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.43 / M
Output price
— / M
$0.87 / M
Context window
—
1,048,576

Individual benchmarks

4 reported for DeepSeek R1 Distill Qwen 14B · 18 for MiMo-V2.6-Pro

No common benchmarks found

DeepSeek R1 Distill Qwen 14B 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

1005.2B diff

MiMo-V2.6-Pro has 1005.2B more parameters than DeepSeek R1 Distill Qwen 14B, making it 6791.9% larger.

DeepSeek
DeepSeek R1 Distill Qwen 14B
14.8Bparameters
Xiaomi
MiMo-V2.6-Pro
1.0Tparameters
14.8B
DeepSeek R1 Distill Qwen 14B
1020.0B
MiMo-V2.6-Pro

Context Window

Maximum input and output token capacity

Only MiMo-V2.6-Pro specifies input context (1,048,576 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 14B
Input- tokens
Output- 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

MiMo-V2.6-Pro supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 14B does not.

MiMo-V2.6-Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Qwen 14B

Text
Images
Audio
Video

MiMo-V2.6-Pro

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

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

DeepSeek R1 Distill Qwen 14B

MIT

Open weights

MiMo-V2.6-Pro

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 14B was released on 2025-01-20, while MiMo-V2.6-Pro was released on 2026-09-22.

MiMo-V2.6-Pro is 20 months newer than DeepSeek R1 Distill Qwen 14B.

DeepSeek R1 Distill Qwen 14B

Jan 20, 2025

1.7 years ago

MiMo-V2.6-Pro

Sep 22, 2026

0 days ago

1.7yr 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek R1 Distill Qwen 14B and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Qwen 14B
✓ Preferred
MiMo-V2.6-Pro
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Qwen 14B vs MiMo-V2.6-Pro.

Which is better, DeepSeek R1 Distill Qwen 14B or MiMo-V2.6-Pro?

MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 10.9. DeepSeek R1 Distill Qwen 14B 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 R1 Distill Qwen 14B compare to MiMo-V2.6-Pro in benchmarks?

DeepSeek R1 Distill Qwen 14B scores MATH-500: 93.9%, AIME 2024: 80.0%, GPQA: 59.1%, LiveCodeBench: 53.1%. 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 R1 Distill Qwen 14B and MiMo-V2.6-Pro?

DeepSeek R1 Distill Qwen 14B supports an unknown number of 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 R1 Distill Qwen 14B and MiMo-V2.6-Pro?

Key differences include LLM Stats Score (10.9 vs 49.8), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Distill Qwen 14B and MiMo-V2.6-Pro?

DeepSeek R1 Distill Qwen 14B is developed by DeepSeek and MiMo-V2.6-Pro is developed by Xiaomi.

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