DeepSeek-V3.2 (Thinking) vs Qwen3 VL 30B A3B Thinking

DeepSeek-V3.2 (Thinking) leads the LLM Stats Score 32.9 to 18.3. DeepSeek-V3.2 (Thinking) is 1.3x cheaper per token.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V3.2 (Thinking) leads the overall LLM Stats Score 32.9 to 18.3, ranking #95 overall.

In the 3 individual benchmarks reported for both models, DeepSeek-V3.2 (Thinking) wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V3.2 (Thinking) is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V3.2 (Thinking)

overall performance matters — it scores 32.9 and ranks #95 on LLM Stats
your work emphasizes reasoning — it leads those capability indexes
you value its reported benchmark strengths — it wins 3 of 3 exact shared results
cost matters — it's about 1.3x cheaper per token
you want the most recent training data — it shipped Dec 2025

Choose Qwen3 VL 30B A3B Thinking

you want predictable pricing at $0.20/M input and $0.99/M output

At a glance

The differences that matter most.

Better token value: DeepSeek-V3.2 (Thinking)

DeepSeek-V3.2 (Thinking)

DeepSeek

Qwen3 VL 30B A3B Thinking

Alibaba Cloud / Qwen Team

Core performance indexes

LLM Stats Score

32.9

#95 · 14 evals

Best

18.3

#202 · 50 evals

Reasoning

32.9

#94 · 13 evals

Best

19.5

#188 · 28 evals

Agents

10.9

#102 · 4 evals

Best

7.9

#127 · 2 evals

Cost, coverage & limits

Benchmark wins

3 of 3

Best

0 of 3

Input price

$0.28 / M

$0.20 / M

Best

Output price

$0.42 / M

Best

$0.99 / M

Context window

131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared

Index

DeepSeek-V3.2 (Thinking)

Qwen3 VL 30B A3B Thinking

Math

30.6#71 · 5 evals

22.5#130 · 11 evals

Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek-V3.2 (Thinking) · 50 for Qwen3 VL 30B A3B Thinking

3 shared

DeepSeek-V3.2 (Thinking) outperforms in 3 benchmarks (AIME 2025, GPQA, MMLU-Pro), while Qwen3 VL 30B A3B Thinking is better at 0 benchmarks.

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

Sun Sep 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

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 1.4x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 2.4x cheaper than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).

In conclusion, Qwen3 VL 30B A3B Thinking is more expensive than DeepSeek-V3.2 (Thinking).*

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

Lowest available price from all providers

Sun Sep 06 2026 • llm-stats.com

DeepSeek-V3.2 (Thinking)

Input tokens$0.28

Output tokens$0.42

Best providerDeepSeek

Qwen3 VL 30B A3B Thinking

Input tokens$0.20

Output tokens$0.99

Best providerNovita

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

654.0B diff

DeepSeek-V3.2 (Thinking) has 654.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 2109.7% larger.

DeepSeek-V3.2 (Thinking)

685.0Bparameters

Qwen3 VL 30B A3B Thinking

31.0Bparameters

685.0B

DeepSeek-V3.2 (Thinking)

31.0B

Qwen3 VL 30B A3B Thinking

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. DeepSeek-V3.2 (Thinking) can generate longer responses up to 65,536 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.

DeepSeek-V3.2 (Thinking)

Input131,072 tokens

Output65,536 tokens

Qwen3 VL 30B A3B Thinking

Input131,072 tokens

Output32,768 tokens

Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas DeepSeek-V3.2 (Thinking) does not.

Qwen3 VL 30B A3B Thinking 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 30B A3B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

DeepSeek-V3.2 (Thinking) is licensed under MIT, while Qwen3 VL 30B A3B Thinking 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 30B A3B Thinking

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 30B A3B Thinking was released on 2025-09-22.

DeepSeek-V3.2 (Thinking) is 2 months newer than Qwen3 VL 30B A3B Thinking.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

9 months ago

2mo newer

Qwen3 VL 30B A3B Thinking

Sep 22, 2025

11 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 30B A3B Thinking is available from Novita, DeepInfra.

DeepSeek-V3.2 (Thinking)

DeepSeek

Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

Qwen3 VL 30B A3B Thinking

Novita

Input Price:Input: $0.20/1MOutput Price:Output: $1.00/1M

Deepinfra

Input Price:Input: $0.29/1MOutput Price:Output: $0.99/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3.2 (Thinking) and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Thinking)

✓ Preferred

Qwen3 VL 30B A3B Thinking

Open in Playground

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs Qwen3 VL 30B A3B Thinking.

Which is better, DeepSeek-V3.2 (Thinking) or Qwen3 VL 30B A3B Thinking?

DeepSeek-V3.2 (Thinking) leads the LLM Stats Score 32.9 to 18.3. DeepSeek-V3.2 (Thinking) is made by DeepSeek and Qwen3 VL 30B A3B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V3.2 (Thinking) compare to Qwen3 VL 30B A3B Thinking 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 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%.

Is DeepSeek-V3.2 (Thinking) cheaper than Qwen3 VL 30B A3B Thinking?

Qwen3 VL 30B A3B Thinking is 1.4x cheaper for input tokens. DeepSeek-V3.2 (Thinking) costs $0.28/M input and $0.42/M output via deepseek. Qwen3 VL 30B A3B Thinking costs $0.20/M input and $0.99/M output via novita.

What are the context window sizes for DeepSeek-V3.2 (Thinking) and Qwen3 VL 30B A3B Thinking?

DeepSeek-V3.2 (Thinking) supports 131K tokens and Qwen3 VL 30B A3B Thinking supports 131K 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 30B A3B Thinking?

Key differences include LLM Stats Score (32.9 vs 18.3), input pricing ($0.28 vs $0.20/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 30B A3B Thinking?

DeepSeek-V3.2 (Thinking) is developed by DeepSeek and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.

DeepSeek-V3.2 (Thinking) vs Qwen3 VL 30B A3B Thinking

Which is better?

Choose DeepSeek-V3.2 (Thinking)

Choose Qwen3 VL 30B A3B Thinking

At a glance

Capability indexes

Individual benchmarks

Human preference

Pricing Analysis

Model Size

Context Window

Input capabilities

DeepSeek-V3.2 (Thinking)

Qwen3 VL 30B A3B Thinking

License

Release Timeline

Knowledge Cutoff

Provider Availability

DeepSeek-V3.2 (Thinking)

Qwen3 VL 30B A3B Thinking

Outputs Comparison

Judge for yourself.

FAQ

Which is better, DeepSeek-V3.2 (Thinking) or Qwen3 VL 30B A3B Thinking?

How does DeepSeek-V3.2 (Thinking) compare to Qwen3 VL 30B A3B Thinking in benchmarks?

Is DeepSeek-V3.2 (Thinking) cheaper than Qwen3 VL 30B A3B Thinking?

What are the context window sizes for DeepSeek-V3.2 (Thinking) and Qwen3 VL 30B A3B Thinking?

What are the main differences between DeepSeek-V3.2 (Thinking) and Qwen3 VL 30B A3B Thinking?

Who makes DeepSeek-V3.2 (Thinking) and Qwen3 VL 30B A3B Thinking?

More DeepSeek-V3.2 (Thinking) comparisons

More Qwen3 VL 30B A3B Thinking comparisons

DeepSeek-V3.2 (Thinking) vs Qwen3 VL 30B A3B Thinking

Which is better?

Choose DeepSeek-V3.2 (Thinking)

Choose Qwen3 VL 30B A3B Thinking

At a glance

Capability indexes

Individual benchmarks

Human preference

Pricing Analysis

Model Size

Context Window

Input capabilities

DeepSeek-V3.2 (Thinking)

Qwen3 VL 30B A3B Thinking

License

Release Timeline

Knowledge Cutoff

Provider Availability

DeepSeek-V3.2 (Thinking)

Qwen3 VL 30B A3B Thinking

Outputs Comparison

Judge for yourself.

Which is better, DeepSeek-V3.2 (Thinking) or Qwen3 VL 30B A3B Thinking?

How does DeepSeek-V3.2 (Thinking) compare to Qwen3 VL 30B A3B Thinking in benchmarks?

Is DeepSeek-V3.2 (Thinking) cheaper than Qwen3 VL 30B A3B Thinking?

What are the context window sizes for DeepSeek-V3.2 (Thinking) and Qwen3 VL 30B A3B Thinking?

What are the main differences between DeepSeek-V3.2 (Thinking) and Qwen3 VL 30B A3B Thinking?

Who makes DeepSeek-V3.2 (Thinking) and Qwen3 VL 30B A3B Thinking?

Related comparisons

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