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DeepSeek V4 Pro vs Qwen-Plus

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for DeepSeek V4 Pro and Qwen-Plus.

DeepSeek

DeepSeek V4 Pro

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

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Alibaba

Qwen-Plus

Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.

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Technical Specifications

SpecificationDeepSeek V4 ProQwen-Plus
ProviderDeepSeekAlibaba
Context Window1,048,576 tokens1,000,000 tokens
Agent Suitability94/100N/A
Time to First Token (TTFT)280 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablebeta
API AvailableYesYes
Released Date2026-04-242025-02-01

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V4 Pro

$0.43

Qwen-Plus

$0.26

Output Price per Million Tokens

DeepSeek V4 Pro

$0.87

Qwen-Plus

$0.78

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8850.0%vs8100.0%
DeepSeek V4 Pro
Qwen-Plus
HumanEvalPython coding & logic synthesis
8900.0%vs8250.0%
DeepSeek V4 Pro
Qwen-Plus
MATHComplex mathematical problem solving
7460.0%vs5500.0%
DeepSeek V4 Pro
Qwen-Plus
GPQAGraduate-level expert reasoning
4900.0%vs3700.0%
DeepSeek V4 Pro
Qwen-Plus
HellaSwagCommonsense reasoning and inference
8750.0%vs8300.0%
DeepSeek V4 Pro
Qwen-Plus
MT-BenchMulti-turn conversation flow quality
918.0%vs865.0%
DeepSeek V4 Pro
Qwen-Plus

DeepSeek V4 Pro Quirks & Gotchas

  • โ–ธMoE architecture โ€” cold-start latency on first request, use keep-alive
  • โ–ธBest cost-performance ratio of any frontier model โ€” strong tool calling for agentic use

Qwen-Plus Quirks & Gotchas

No developer gotchas reported.