Model Comparison

DeepSeek-V3.2 (Thinking) vs Qwen3 VL 235B A22B InstructWhich is better in 2026?

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is 1.9x cheaper per token.

Verdict: DeepSeek-V3.2 (Thinking) vs Qwen3 VL 235B A22B Instruct — which is better?

DeepSeek-V3.2 (Thinking) (by DeepSeek) and Qwen3 VL 235B A22B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-V3.2 (Thinking) outperforms in 2 benchmarks (AIME 2025, MMLU-Pro), while Qwen3 VL 235B A22B Instruct is better at 0 benchmarks. DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

On price, DeepSeek-V3.2 (Thinking) is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3 VL 235B A22B Instruct also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek-V3.2 (Thinking) if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • cost matters — it's about 1.9x cheaper per token
  • you want the most recent training data — it shipped Dec 2025

Choose Qwen3 VL 235B A22B Instruct if…

  • you process long inputs — it offers a 262,144 token context window

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2 (Thinking) outperforms in 2 benchmarks (AIME 2025, MMLU-Pro), while Qwen3 VL 235B A22B Instruct is better at 0 benchmarks.

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

Tue Jul 28 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2 (Thinking) costs less

For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 1.1x cheaper than Qwen3 VL 235B A22B Instruct ($0.30/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 3.5x cheaper than Qwen3 VL 235B A22B Instruct ($1.49/1M tokens).

In conclusion, Qwen3 VL 235B A22B Instruct is more expensive than DeepSeek-V3.2 (Thinking).*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Jul 28 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Instruct
Input tokens$0.30
Output tokens$1.49
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

449.0B diff

DeepSeek-V3.2 (Thinking) has 449.0B more parameters than Qwen3 VL 235B A22B Instruct, making it 190.3% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Instruct
236.0Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
236.0B
Qwen3 VL 235B A22B Instruct

Context Window

Maximum input and output token capacity

Qwen3 VL 235B A22B Instruct accepts 262,144 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. Qwen3 VL 235B A22B Instruct can generate longer responses up to 262,144 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Instruct
Input262,144 tokens
Output262,144 tokens
Tue Jul 28 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 235B A22B Instruct supports multimodal inputs, whereas DeepSeek-V3.2 (Thinking) does not.

Qwen3 VL 235B A22B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2 (Thinking)

Text
Images
Audio
Video

Qwen3 VL 235B A22B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while Qwen3 VL 235B A22B Instruct uses Apache 2.0.

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

DeepSeek-V3.2 (Thinking)

MIT

Open weights

Qwen3 VL 235B A22B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while Qwen3 VL 235B A22B Instruct was released on 2025-09-22.

DeepSeek-V3.2 (Thinking) is 2 months newer than Qwen3 VL 235B A22B Instruct.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

7 months ago

2mo newer
Qwen3 VL 235B A22B Instruct

Sep 22, 2025

10 months 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

Provider Availability

DeepSeek-V3.2 (Thinking) is available from DeepSeek. Qwen3 VL 235B A22B Instruct is available from DeepInfra, Novita.

DeepSeek-V3.2 (Thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

Qwen3 VL 235B A22B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.30/1MOutput Price:Output: $1.49/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.50/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Less expensive input tokens
Less expensive output tokens
Higher AIME 2025 score (93.1% vs 74.7%)
Higher MMLU-Pro score (85.0% vs 81.8%)
Larger context window (262,144 tokens)
Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V3.2 (Thinking) and Qwen3 VL 235B A22B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Thinking)
✓ Preferred
Qwen3 VL 235B A22B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs Qwen3 VL 235B A22B Instruct.

Which is better, DeepSeek-V3.2 (Thinking) or Qwen3 VL 235B A22B Instruct?

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is made by DeepSeek and Qwen3 VL 235B A22B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.2 (Thinking) compare to Qwen3 VL 235B A22B Instruct in benchmarks?

DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. Qwen3 VL 235B A22B Instruct scores DocVQAtest: 97.1%, ScreenSpot: 95.4%, MMLU-Redux: 92.2%, OCRBench: 92.0%, MMBench-V1.1: 89.9%.

Is DeepSeek-V3.2 (Thinking) cheaper than Qwen3 VL 235B A22B Instruct?

DeepSeek-V3.2 (Thinking) is 1.1x cheaper for input tokens. DeepSeek-V3.2 (Thinking) costs $0.28/M input and $0.42/M output via deepseek. Qwen3 VL 235B A22B Instruct costs $0.30/M input and $1.49/M output via deepinfra.

What are the context window sizes for DeepSeek-V3.2 (Thinking) and Qwen3 VL 235B A22B Instruct?

DeepSeek-V3.2 (Thinking) supports 131K tokens and Qwen3 VL 235B A22B Instruct supports 262K 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 (Thinking) and Qwen3 VL 235B A22B Instruct?

Key differences include context window (131K vs 262K), input pricing ($0.28 vs $0.30/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Thinking) and Qwen3 VL 235B A22B Instruct?

DeepSeek-V3.2 (Thinking) is developed by DeepSeek and Qwen3 VL 235B A22B Instruct is developed by Alibaba Cloud / Qwen Team.