Model Comparison

DeepSeek R1 Distill Llama 70B vs Qwen2.5 VL 72B Instruct

Comparing DeepSeek R1 Distill Llama 70B and Qwen2.5 VL 72B Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Llama 70B and Qwen2.5 VL 72B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Fri Apr 03 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Llama 70B
Input tokens$0.10
Output tokens$0.40
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

1.4B diff

Qwen2.5 VL 72B Instruct has 1.4B more parameters than DeepSeek R1 Distill Llama 70B, making it 2.0% larger.

DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
72.0Bparameters
70.6B
DeepSeek R1 Distill Llama 70B
72.0B
Qwen2.5 VL 72B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek R1 Distill Llama 70B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Llama 70B specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 VL 72B Instruct
Input- tokens
Output- tokens
Fri Apr 03 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 72B Instruct supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.

Qwen2.5 VL 72B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Llama 70B

Text
Images
Audio
Video

Qwen2.5 VL 72B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Distill Llama 70B is licensed under MIT, while Qwen2.5 VL 72B Instruct uses tongyi-qianwen.

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

DeepSeek R1 Distill Llama 70B

MIT

Open weights

Qwen2.5 VL 72B Instruct

tongyi-qianwen

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Qwen2.5 VL 72B Instruct was released on 2025-01-26.

Qwen2.5 VL 72B Instruct is 0 month newer than DeepSeek R1 Distill Llama 70B.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.2 years ago

Qwen2.5 VL 72B Instruct

Jan 26, 2025

1.2 years ago

6d 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

Key Takeaways

Larger context window (128,000 tokens)
Alibaba Cloud / Qwen Team

Qwen2.5 VL 72B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs Qwen2.5 VL 72B Instruct

DeepSeek R1 Distill Llama 70B (DeepSeek) and Qwen2.5 VL 72B Instruct (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. Qwen2.5 VL 72B Instruct scores DocVQA: 96.4%, Android Control Low_EM: 93.7%, ChartQA: 89.5%, OCRBench: 88.5%, AI2D: 88.4%.
DeepSeek R1 Distill Llama 70B supports 128K tokens and Qwen2.5 VL 72B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs tongyi-qianwen). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Distill Llama 70B is developed by DeepSeek and Qwen2.5 VL 72B Instruct is developed by Alibaba Cloud / Qwen Team.