Model Comparison

Qwen3 VL 30B A3B Thinking vs Qwen3 VL 4B ThinkingWhich is better in 2026?

Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks. Qwen3 VL 4B Thinking is 1.2x cheaper per token.

Verdict: Qwen3 VL 30B A3B Thinking vs Qwen3 VL 4B Thinking — which is better?

Qwen3 VL 30B A3B Thinking (by Alibaba Cloud / Qwen Team) and Qwen3 VL 4B Thinking (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.

Qwen3 VL 30B A3B Thinking outperforms in 44 benchmarks (AI2D, AIME 2025, Arena-Hard v2, BFCL-v3, BLINK, CC-OCR, CharadesSTA, CharXiv-D, CharXiv-R, Creative Writing v3, DocVQAtest, GPQA, Hallusion Bench, HMMT25, Include, InfoVQAtest, LiveBench 20241125, LiveCodeBench v6, LVBench, MathVision, MathVista-Mini, MLVU-M, MMBench-V1.1, MMLU, MMLU-Pro, MMLU-ProX, MMLU-Redux, MM-MT-Bench, MMMU-Pro, MMMU (val), MMStar, MuirBench, MVBench, OCRBench, OCRBench-V2 (en), OCRBench-V2 (zh), ODinW, PolyMATH, RealWorldQA, ScreenSpot, ScreenSpot Pro, SuperGPQA, VideoMMMU, WritingBench), while Qwen3 VL 4B Thinking is better at 4 benchmarks (ERQA, IFEval, Multi-IF, OSWorld). Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks.

On price, Qwen3 VL 4B Thinking is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3 VL 4B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose Qwen3 VL 30B A3B Thinking if…

  • you want the strongest raw capability — it leads on 44 of 48 shared benchmarks

Choose Qwen3 VL 4B Thinking if…

  • cost matters — it's about 1.2x cheaper per token
  • you process long inputs — it offers a 262,144 token context window

Performance Benchmarks

Comparative analysis across standard metrics

48 benchmarks

Qwen3 VL 30B A3B Thinking outperforms in 44 benchmarks (AI2D, AIME 2025, Arena-Hard v2, BFCL-v3, BLINK, CC-OCR, CharadesSTA, CharXiv-D, CharXiv-R, Creative Writing v3, DocVQAtest, GPQA, Hallusion Bench, HMMT25, Include, InfoVQAtest, LiveBench 20241125, LiveCodeBench v6, LVBench, MathVision, MathVista-Mini, MLVU-M, MMBench-V1.1, MMLU, MMLU-Pro, MMLU-ProX, MMLU-Redux, MM-MT-Bench, MMMU-Pro, MMMU (val), MMStar, MuirBench, MVBench, OCRBench, OCRBench-V2 (en), OCRBench-V2 (zh), ODinW, PolyMATH, RealWorldQA, ScreenSpot, ScreenSpot Pro, SuperGPQA, VideoMMMU, WritingBench), while Qwen3 VL 4B Thinking is better at 4 benchmarks (ERQA, IFEval, Multi-IF, OSWorld).

Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks.

Sun Jul 26 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 4B Thinking costs less

For input processing, Qwen3 VL 30B A3B Thinking ($0.20/1M tokens) is 2.0x more expensive than Qwen3 VL 4B Thinking ($0.10/1M tokens).

For output processing, Qwen3 VL 30B A3B Thinking ($0.99/1M tokens) is 1.0x cheaper than Qwen3 VL 4B Thinking ($1.00/1M tokens).

In conclusion, Qwen3 VL 30B A3B Thinking is more expensive than Qwen3 VL 4B Thinking.*

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

Lowest available price from all providers
Sun Jul 26 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input tokens$0.20
Output tokens$0.99
Best providerNovita
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input tokens$0.10
Output tokens$1.00
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

27.0B diff

Qwen3 VL 30B A3B Thinking has 27.0B more parameters than Qwen3 VL 4B Thinking, making it 675.0% larger.

Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
31.0B
Qwen3 VL 30B A3B Thinking
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 4B Thinking accepts 262,144 input tokens compared to Qwen3 VL 30B A3B Thinking's 131,072 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.

Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Sun Jul 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Qwen3 VL 30B A3B Thinking and Qwen3 VL 4B Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Qwen3 VL 30B A3B Thinking

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Both models were released on 2025-09-22.

They likely represent similar generations of model development.

Qwen3 VL 30B A3B Thinking

Sep 22, 2025

10 months ago

Qwen3 VL 4B Thinking

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

Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra. Qwen3 VL 4B Thinking is available from DeepInfra.

Qwen3 VL 30B A3B Thinking

novita logo
Novita
Input Price:Input: $0.20/1MOutput Price:Output: $1.00/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.29/1MOutput Price:Output: $0.99/1M

Qwen3 VL 4B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $1.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Alibaba Cloud / Qwen Team

Qwen3 VL 30B A3B Thinking

View details

Alibaba Cloud / Qwen Team

Less expensive output tokens
Higher AI2D score (86.9% vs 84.9%)
Higher AIME 2025 score (83.1% vs 74.5%)
Higher Arena-Hard v2 score (56.7% vs 36.8%)
Higher BFCL-v3 score (68.6% vs 67.3%)
Higher BLINK score (65.4% vs 63.4%)
Higher CC-OCR score (77.8% vs 73.8%)
Higher CharadesSTA score (62.7% vs 59.0%)
Higher CharXiv-D score (86.9% vs 83.9%)
Higher CharXiv-R score (56.6% vs 50.3%)
Higher Creative Writing v3 score (82.5% vs 76.1%)
Higher DocVQAtest score (95.0% vs 94.2%)
Higher GPQA score (74.4% vs 64.1%)
Higher Hallusion Bench score (66.0% vs 64.1%)
Higher HMMT25 score (67.6% vs 53.1%)
Higher Include score (74.5% vs 64.6%)
Higher InfoVQAtest score (86.0% vs 83.0%)
Higher LiveBench 20241125 score (72.1% vs 68.4%)
Higher LiveCodeBench v6 score (64.2% vs 51.3%)
Higher LVBench score (59.2% vs 53.5%)
Higher MathVision score (65.7% vs 60.0%)
Higher MathVista-Mini score (81.9% vs 79.5%)
Higher MLVU-M score (78.9% vs 75.7%)
Higher MMBench-V1.1 score (88.9% vs 86.7%)
Higher MMLU score (87.6% vs 81.5%)
Higher MMLU-Pro score (80.5% vs 73.6%)
Higher MMLU-ProX score (76.1% vs 65.0%)
Higher MMLU-Redux score (90.9% vs 86.0%)
Higher MM-MT-Bench score (7.9% vs 7.7%)
Higher MMMU-Pro score (63.0% vs 57.0%)
Higher MMMU (val) score (76.0% vs 70.8%)
Higher MMStar score (75.5% vs 73.2%)
Higher MuirBench score (77.6% vs 75.0%)
Higher MVBench score (72.0% vs 69.3%)
Higher OCRBench score (83.9% vs 80.8%)
Higher OCRBench-V2 (en) score (62.6% vs 61.8%)
Higher OCRBench-V2 (zh) score (60.4% vs 55.8%)
Higher ODinW score (42.3% vs 39.4%)
Higher PolyMATH score (51.7% vs 44.6%)
Higher RealWorldQA score (77.4% vs 73.2%)
Higher ScreenSpot score (94.7% vs 92.9%)
Higher ScreenSpot Pro score (57.3% vs 49.2%)
Higher SuperGPQA score (56.4% vs 46.8%)
Higher VideoMMMU score (75.0% vs 69.4%)
Higher WritingBench score (85.2% vs 84.0%)
Alibaba Cloud / Qwen Team

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Less expensive input tokens
Higher ERQA score (47.3% vs 45.3%)
Higher IFEval score (82.6% vs 81.7%)
Higher Multi-IF score (73.6% vs 73.0%)
Higher OSWorld score (31.4% vs 30.6%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Qwen3 VL 30B A3B Thinking and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.

Qwen3 VL 30B A3B Thinking
✓ Preferred
Qwen3 VL 4B Thinking
Open in Playground
AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking

FAQ

Common questions about Qwen3 VL 30B A3B Thinking vs Qwen3 VL 4B Thinking.

Which is better, Qwen3 VL 30B A3B Thinking or Qwen3 VL 4B Thinking?

Qwen3 VL 30B A3B Thinking significantly outperforms across most benchmarks. Qwen3 VL 30B A3B Thinking is made by Alibaba Cloud / Qwen Team and Qwen3 VL 4B Thinking 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 Qwen3 VL 30B A3B Thinking compare to Qwen3 VL 4B Thinking in benchmarks?

Qwen3 VL 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.

Is Qwen3 VL 30B A3B Thinking cheaper than Qwen3 VL 4B Thinking?

Qwen3 VL 4B Thinking is 2.0x cheaper for input tokens. Qwen3 VL 30B A3B Thinking costs $0.20/M input and $0.99/M output via novita. Qwen3 VL 4B Thinking costs $0.10/M input and $1.00/M output via deepinfra.

What are the context window sizes for Qwen3 VL 30B A3B Thinking and Qwen3 VL 4B Thinking?

Qwen3 VL 30B A3B Thinking supports 131K tokens and Qwen3 VL 4B Thinking 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 Qwen3 VL 30B A3B Thinking and Qwen3 VL 4B Thinking?

Key differences include context window (131K vs 262K), input pricing ($0.20 vs $0.10/M). See the full comparison above for benchmark-by-benchmark results.