Model Comparison

DeepSeek VL2 vs Qwen3-Next-80B-A3B-Thinking

Comparing DeepSeek VL2 and Qwen3-Next-80B-A3B-Thinking across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Qwen3-Next-80B-A3B-Thinking 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
Sat Apr 11 2026 • llm-stats.com
DeepSeek
DeepSeek VL2
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
Input tokens$0.15
Output tokens$1.50
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

53.0B diff

Qwen3-Next-80B-A3B-Thinking has 53.0B more parameters than DeepSeek VL2, making it 196.3% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
80.0Bparameters
27.0B
DeepSeek VL2
80.0B
Qwen3-Next-80B-A3B-Thinking

Context Window

Maximum input and output token capacity

DeepSeek VL2 accepts 129,280 input tokens compared to Qwen3-Next-80B-A3B-Thinking's 65,536 tokens. DeepSeek VL2 can generate longer responses up to 129,280 tokens, while Qwen3-Next-80B-A3B-Thinking is limited to 65,536 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
Input65,536 tokens
Output65,536 tokens
Sat Apr 11 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas Qwen3-Next-80B-A3B-Thinking does not.

DeepSeek VL2 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2

Text
Images
Audio
Video

Qwen3-Next-80B-A3B-Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Qwen3-Next-80B-A3B-Thinking uses Apache 2.0.

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

DeepSeek VL2

deepseek

Open weights

Qwen3-Next-80B-A3B-Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Qwen3-Next-80B-A3B-Thinking was released on 2025-09-10.

Qwen3-Next-80B-A3B-Thinking is 9 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.3 years ago

Qwen3-Next-80B-A3B-Thinking

Sep 10, 2025

7 months ago

9mo 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. Qwen3-Next-80B-A3B-Thinking is available from Novita.

DeepSeek VL2

replicate logo
Replicate

Qwen3-Next-80B-A3B-Thinking

novita logo
Novita
Input Price:Input: $0.15/1MOutput Price:Output: $1.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (129,280 tokens)
Supports multimodal inputs
Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking

FAQ

Common questions about DeepSeek VL2 vs Qwen3-Next-80B-A3B-Thinking

DeepSeek VL2 (DeepSeek) and Qwen3-Next-80B-A3B-Thinking (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 VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Qwen3-Next-80B-A3B-Thinking scores MMLU-Redux: 92.5%, IFEval: 88.9%, AIME 2025: 87.8%, WritingBench: 84.6%, MMLU-Pro: 82.7%.
DeepSeek VL2 supports 129K tokens and Qwen3-Next-80B-A3B-Thinking supports 66K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (129K vs 66K), multimodal support (yes vs no), licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek VL2 is developed by DeepSeek and Qwen3-Next-80B-A3B-Thinking is developed by Alibaba Cloud / Qwen Team.