DeepSeek R1 Distill Llama 70B vs Qwen2.5 VL 32B Instruct
DeepSeek R1 Distill Llama 70B leads the LLM Stats Score 14.7 to 10.0.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek R1 Distill Llama 70B leads the overall LLM Stats Score 14.7 to 10.0, ranking #218 overall.
In the 1 individual benchmarks reported for both models, DeepSeek R1 Distill Llama 70B wins 1; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Llama 70B
- overall performance matters — it scores 14.7 and ranks #218 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
Choose Qwen2.5 VL 32B Instruct
- you want the most recent training data — it shipped Feb 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
4 reported for DeepSeek R1 Distill Llama 70B · 28 for Qwen2.5 VL 32B Instruct
DeepSeek R1 Distill Llama 70B outperforms in 1 benchmarks (GPQA), while Qwen2.5 VL 32B Instruct is better at 0 benchmarks.
DeepSeek R1 Distill Llama 70B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek R1 Distill Llama 70B has 37.1B more parameters than Qwen2.5 VL 32B Instruct, making it 110.7% larger.
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).
Input capabilities
Documented input modalities across available providers
Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.
Qwen2.5 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Llama 70B
Qwen2.5 VL 32B Instruct
License
Usage and distribution terms
DeepSeek R1 Distill Llama 70B is licensed under MIT, while Qwen2.5 VL 32B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.
Qwen2.5 VL 32B Instruct is 1 month newer than DeepSeek R1 Distill Llama 70B.
Jan 20, 2025
1.6 years ago
Feb 28, 2025
1.5 years ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Llama 70B and Qwen2.5 VL 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Llama 70B vs Qwen2.5 VL 32B Instruct.