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DeepSeek-V3.2-Speciale vs Qwen2 72B Instruct

DeepSeek-V3.2-Speciale leads the LLM Stats Score 34.3 to 6.0.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V3.2-Speciale leads the overall LLM Stats Score 34.3 to 6.0, ranking #87 overall.

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

Choose DeepSeek-V3.2-Speciale

  • overall performance matters — it scores 34.3 and ranks #87 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Dec 2025

Choose Qwen2 72B Instruct

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

At a glance

The differences that matter most.

DeepSeek-V3.2-Speciale
DeepSeek
Qwen2 72B Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
34.3
#87
6.0
#283
Reasoning
32.9
#95
5.8
#279
Coding
18.4
#105
9.9
#161
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.28 / M
— / M
Output price
$0.42 / M
— / M
Context window
131,072
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3.2-Speciale
Qwen2 72B Instruct
Math
35.1#43
11.3#238
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for DeepSeek-V3.2-Speciale · 17 for Qwen2 72B Instruct

No common benchmarks found

DeepSeek-V3.2-Speciale and Qwen2 72B Instructdon'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

613.0B diff

DeepSeek-V3.2-Speciale has 613.0B more parameters than Qwen2 72B Instruct, making it 851.4% larger.

DeepSeek
DeepSeek-V3.2-Speciale
685.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2 72B Instruct
72.0Bparameters
685.0B
DeepSeek-V3.2-Speciale
72.0B
Qwen2 72B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Speciale specifies input context (131,072 tokens). Only DeepSeek-V3.2-Speciale specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3.2-Speciale
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2 72B Instruct
Input- tokens
Output- tokens
Mon Sep 07 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Speciale is licensed under MIT, while Qwen2 72B Instruct uses tongyi-qianwen.

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

DeepSeek-V3.2-Speciale

MIT

Open weights

Qwen2 72B Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Speciale was released on 2025-12-01, while Qwen2 72B Instruct was released on 2024-07-23.

DeepSeek-V3.2-Speciale is 17 months newer than Qwen2 72B Instruct.

DeepSeek-V3.2-Speciale

Dec 1, 2025

9 months ago

1.4yr newer
Qwen2 72B Instruct

Jul 23, 2024

2.1 years 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3.2-Speciale and Qwen2 72B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V3.2-Speciale
✓ Preferred
Qwen2 72B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V3.2-Speciale vs Qwen2 72B Instruct.

Which is better, DeepSeek-V3.2-Speciale or Qwen2 72B Instruct?

DeepSeek-V3.2-Speciale leads the LLM Stats Score 34.3 to 6.0. DeepSeek-V3.2-Speciale is made by DeepSeek and Qwen2 72B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V3.2-Speciale compare to Qwen2 72B Instruct in benchmarks?

DeepSeek-V3.2-Speciale scores HMMT 2025: 99.2%, AIME 2025: 96.0%, CodeForces: 90.0%, t2-bench: 80.3%, SWE-Bench Verified: 73.1%. Qwen2 72B Instruct scores GSM8k: 91.1%, CMMLU: 90.1%, HellaSwag: 87.6%, HumanEval: 86.0%, Winogrande: 85.1%.

What are the context window sizes for DeepSeek-V3.2-Speciale and Qwen2 72B Instruct?

DeepSeek-V3.2-Speciale supports 131K tokens and Qwen2 72B Instruct supports an unknown number of 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-Speciale and Qwen2 72B Instruct?

Key differences include LLM Stats Score (34.3 vs 6.0), licensing (MIT vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2-Speciale and Qwen2 72B Instruct?

DeepSeek-V3.2-Speciale is developed by DeepSeek and Qwen2 72B Instruct is developed by Alibaba Cloud / Qwen Team.

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