Model Comparison

Mercury 2 vs Qwen3 VL 30B A3B Thinking

Both models are evenly matched across the benchmarks. Mercury 2 is 1.1x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Mercury 2 outperforms in 1 benchmarks (AIME 2025), while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (GPQA).

Both models are evenly matched across the benchmarks.

Tue Apr 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Mercury 2 costs less

For input processing, Mercury 2 ($0.25/1M tokens) is 1.3x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).

For output processing, Mercury 2 ($0.75/1M tokens) is 1.3x cheaper than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).

In conclusion, Qwen3 VL 30B A3B Thinking is more expensive than Mercury 2.*

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

Lowest available price from all providers

Tue Apr 14 2026 • llm-stats.com

Mercury 2

Input tokens$0.25

Output tokens$0.75

Best providerInception

Qwen3 VL 30B A3B Thinking

Input tokens$0.20

Output tokens$0.99

Best providerNovita

Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Qwen3 VL 30B A3B Thinking accepts 131,072 input tokens compared to Mercury 2's 128,000 tokens. Qwen3 VL 30B A3B Thinking can generate longer responses up to 32,768 tokens, while Mercury 2 is limited to 8,192 tokens.

Mercury 2

Input128,000 tokens

Output8,192 tokens

Qwen3 VL 30B A3B Thinking

Input131,072 tokens

Output32,768 tokens

Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas Mercury 2 does not.

Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Mercury 2

Text

Images

Audio

Video

Qwen3 VL 30B A3B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Mercury 2 is licensed under a proprietary license, 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.

Mercury 2

Proprietary

Closed source

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Mercury 2 was released on 2026-02-24, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.

Mercury 2 is 5 months newer than Qwen3 VL 30B A3B Thinking.

Mercury 2

Feb 24, 2026

1 months ago

5mo newer

Qwen3 VL 30B A3B Thinking

Sep 22, 2025

6 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

Mercury 2 is available from Inception. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.

Mercury 2

Inception

Input Price:Input: $0.25/1MOutput Price:Output: $0.75/1M

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

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Key Takeaways

Mercury 2

View details

Inception

Less expensive output tokens

Higher AIME 2025 score (91.1% vs 83.1%)

Qwen3 VL 30B A3B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (131,072 tokens)

Supports multimodal inputs

Less expensive input tokens

Has open weights

Higher GPQA score (74.4% vs 74.0%)

Detailed Comparison

AI Model Comparison Table
Feature	Mercury 2	Qwen3 VL 30B A3B Thinking

FAQ

Common questions about Mercury 2 vs Qwen3 VL 30B A3B Thinking

Both models are evenly matched across the benchmarks. Mercury 2 is made by Inception and Qwen3 VL 30B A3B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

Mercury 2 scores AIME 2025: 91.1%, GPQA: 74.0%, IFBench: 71.0%, LiveCodeBench: 67.0%, Tau2 Airline: 53.0%. 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 30B A3B Thinking is 1.3x cheaper for input tokens. Mercury 2 costs $0.25/M input and $0.75/M output via inception. Qwen3 VL 30B A3B Thinking costs $0.20/M input and $0.99/M output via novita.

Mercury 2 supports 128K 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.

Key differences include context window (128K vs 131K), input pricing ($0.25 vs $0.20/M), multimodal support (no vs yes), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Mercury 2 is developed by Inception and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.

Mercury 2 vs Qwen3 VL 30B A3B Thinking

Performance Benchmarks

Arena Performance

Pricing Analysis

Context Window

Input Capabilities

Mercury 2

Qwen3 VL 30B A3B Thinking

License

Release Timeline

Knowledge Cutoff

Provider Availability

Mercury 2

Qwen3 VL 30B A3B Thinking

Outputs Comparison

Key Takeaways

Mercury 2

Qwen3 VL 30B A3B Thinking

Detailed Comparison

FAQ

Which is better, Mercury 2 or Qwen3 VL 30B A3B Thinking?

How does Mercury 2 compare to Qwen3 VL 30B A3B Thinking in benchmarks?

Is Mercury 2 cheaper than Qwen3 VL 30B A3B Thinking?

What are the context window sizes for Mercury 2 and Qwen3 VL 30B A3B Thinking?

What are the main differences between Mercury 2 and Qwen3 VL 30B A3B Thinking?

Who makes Mercury 2 and Qwen3 VL 30B A3B Thinking?