Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning): The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) Showdown

After a comprehensive analysis, Magistral Medium 1.2 emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, Qwen3 VL 30B A3B (Reasoning) remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) comparison will break down every critical metric to help you make the best decision.

Explore best-for scenarios•Let the AI Selector recommend next steps

Model Snapshot

Key decision metrics at a glance.

Magistral Medium 1.2

Mistral

Reasoning: 8
Coding: 2
Multimodal: 2
Long Context: 3
Blended Price / 1M tokens: $0.003
P95 Latency: 1000ms
Tokens per second: 31.19tokens/sec

Qwen3 VL 30B A3B (Reasoning)

Other

Reasoning: 8
Coding: 1
Multimodal: 2
Long Context: 2
Blended Price / 1M tokens: $0.001
P95 Latency: 1000ms
Tokens per second: 119.551tokens/sec

Overall Capabilities

The capability radar provides a holistic view of the Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) matchup. This chart illustrates each model's strengths and weaknesses at a glance, forming a cornerstone of our Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) analysis.

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `Magistral Medium 1.2` vs `Qwen3 VL 30B A3B (Reasoning)`.

Benchmark Breakdown

For a granular look, this chart directly compares scores across standardized benchmarks. In the critical MMLU Pro test, a key part of the Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) debate, Magistral Medium 1.2 scores 80 against Qwen3 VL 30B A3B (Reasoning)'s 80. This data-driven approach is essential for any serious Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) comparison.

This grouped bar chart provides a side-by-side comparison for each benchmark metric.

Speed & Latency

Speed is a crucial factor in the Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) decision for interactive applications. The metrics below highlight the trade-offs you should weigh before shipping to production.

Time to First Token

Magistral Medium 1.2300ms

Qwen3 VL 30B A3B (Reasoning)300ms

Tokens per Second

Magistral Medium 1.231.19

Qwen3 VL 30B A3B (Reasoning)119.551

Head to the playground to validate these results yourself

The Economics of Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning)

Power is only one part of the equation. This Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) pricing analysis gives you a true sense of value.

Pricing Breakdown

Compare input and output pricing at a glance.

Real-World Cost Scenario

To process 1M input tokens and generate 250k output tokens, Magistral Medium 1.2 would cost $0.003, whereas Qwen3 VL 30B A3B (Reasoning) would cost $0.001. This practical calculation is vital for any developer considering the Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) choice.

Review the complete pricing and packaging strategy

Which Model Wins the Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) Battle for You?

Choose Magistral Medium 1.2 if...

Your top priority is raw performance and capability.

Cost is a secondary concern to power in your Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) decision.

You need the most advanced reasoning capabilities available.

Choose Qwen3 VL 30B A3B (Reasoning) if...

You need a highly responsive model for user-facing applications.

Your budget is a primary consideration in the Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) choice.

You are developing at scale where operational costs are critical.

Explore all Best picks Use the AI Selector for a tailored recommendation

Your Questions about the Magistral Medium 1.2 vs Qwen3 VL 30B A3B (Reasoning) Comparison

Review the full evaluation methodology · Read the latest analysis posts

Data source: https://artificialanalysis.ai/