Model Comparison

DeepSeek VL2 vs Qwen3-235B-A22B-Instruct-2507

Comparing DeepSeek VL2 and Qwen3-235B-A22B-Instruct-2507 across benchmarks, pricing, and capabilities.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and Qwen3-235B-A22B-Instruct-2507 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
Wed Apr 29 2026 • llm-stats.com
DeepSeek
DeepSeek VL2
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input tokens$0.15
Output tokens$0.80
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

208.0B diff

Qwen3-235B-A22B-Instruct-2507 has 208.0B more parameters than DeepSeek VL2, making it 770.4% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
235.0Bparameters
27.0B
DeepSeek VL2
235.0B
Qwen3-235B-A22B-Instruct-2507

Context Window

Maximum input and output token capacity

Qwen3-235B-A22B-Instruct-2507 accepts 262,144 input tokens compared to DeepSeek VL2's 129,280 tokens. Qwen3-235B-A22B-Instruct-2507 can generate longer responses up to 131,072 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output131,072 tokens
Wed Apr 29 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 supports multimodal inputs, whereas Qwen3-235B-A22B-Instruct-2507 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

Qwen3-235B-A22B-Instruct-2507

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Qwen3-235B-A22B-Instruct-2507 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

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

Qwen3-235B-A22B-Instruct-2507 is 7 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.4 years ago

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

9 months ago

7mo 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. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.

DeepSeek VL2

replicate logo
Replicate

Qwen3-235B-A22B-Instruct-2507

fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M
novita logo
Novita
Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Supports multimodal inputs
Alibaba Cloud / Qwen Team
Larger context window (262,144 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507

FAQ

Common questions about DeepSeek VL2 vs Qwen3-235B-A22B-Instruct-2507

DeepSeek VL2 (DeepSeek) and Qwen3-235B-A22B-Instruct-2507 (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%. Qwen3-235B-A22B-Instruct-2507 scores ZebraLogic: 95.0%, MMLU-Redux: 93.1%, IFEval: 88.7%, MultiPL-E: 87.9%, Creative Writing v3: 87.5%.
DeepSeek VL2 supports 129K tokens and Qwen3-235B-A22B-Instruct-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (129K vs 262K), 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 Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.