DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct: The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct Showdown

After a comprehensive analysis, DeepSeek V3.2 (Reasoning) emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, Qwen3 30B A3B 2507 Instruct remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct 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.

DeepSeek V3.2 (Reasoning)

DeepSeek

Reasoning: 9
Coding: 4
Multimodal: 3
Long Context: 5
Blended Price / 1M tokens: $0.000
P95 Latency: 1000ms
Tokens per second: 31.585tokens/sec

Qwen3 30B A3B 2507 Instruct

Other

Reasoning: 7
Coding: 1
Multimodal: 1
Long Context: 2
Blended Price / 1M tokens: $0.000
P95 Latency: 1000ms
Tokens per second: 58.089tokens/sec

Overall Capabilities

The capability radar provides a holistic view of the DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct matchup. This chart illustrates each model's strengths and weaknesses at a glance, forming a cornerstone of our DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct analysis.

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `DeepSeek V3.2 (Reasoning)` vs `Qwen3 30B A3B 2507 Instruct`.

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 DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct debate, DeepSeek V3.2 (Reasoning) scores 90 against Qwen3 30B A3B 2507 Instruct's 70. This data-driven approach is essential for any serious DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct comparison.

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

Speed & Latency

Speed is a crucial factor in the DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct decision for interactive applications. The metrics below highlight the trade-offs you should weigh before shipping to production.

Time to First Token

DeepSeek V3.2 (Reasoning)300ms

Qwen3 30B A3B 2507 Instruct300ms

Tokens per Second

DeepSeek V3.2 (Reasoning)31.585

Qwen3 30B A3B 2507 Instruct58.089

Head to the playground to validate these results yourself

The Economics of DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct

Power is only one part of the equation. This DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct 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, DeepSeek V3.2 (Reasoning) would cost $0.000, whereas Qwen3 30B A3B 2507 Instruct would cost $0.000. This practical calculation is vital for any developer considering the DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct choice.

Review the complete pricing and packaging strategy

Which Model Wins the DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct Battle for You?

Choose DeepSeek V3.2 (Reasoning) if...

Your top priority is raw performance and capability.

You are working in a technical or scientific field requiring the highest accuracy.

You need the most advanced reasoning capabilities available.

Choose Qwen3 30B A3B 2507 Instruct if...

You are developing at scale where operational costs are critical.

You prioritize cost-effectiveness over maximum performance.

Your workload requires consistent, reliable performance.

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

Your Questions about the DeepSeek V3.2 (Reasoning) vs Qwen3 30B A3B 2507 Instruct Comparison

Review the full evaluation methodology · Read the latest analysis posts

Data source: https://artificialanalysis.ai/