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Discover how DeepSeek's DeepSeek V4 Pro and Alibaba's Qwen3.8-Max stack up against each other in this comprehensive comparison of two leading AI language models.

Explore their capabilities, pricing, and performance metrics, with DeepSeek V4 Pro achieving 90.1% on GPQA Diamond and Qwen3.8-Max scoring 92.6%, making this comparison essential for developers and organizations seeking the right AI solution for their specific needs.

Models Overview

	DeepSeek V4 Pro	Qwen3.8-Max
Provider The company that provides the model.	DeepSeek	Alibaba
Context Length Maximum number of tokens the model can process	1M	1M
Maximum Output Maximum number of tokens the model can generate in one response	384K	131.07K
Release Date When the model was first released.	Unknown	02-09-2026
Knowledge Cutoff When the model's training data ends.	Unknown	Unknown
Open Source Whether the model weights are openly available.	TRUE	TRUE

Pricing Comparison

Compare the pricing of DeepSeek's DeepSeek V4 Pro and Alibaba's Qwen3.8-Max to determine the most cost-effective solution for your AI needs. Prices are the standard API tier per million tokens, as published by each provider as of September 2026.

	DeepSeek V4 Pro	Qwen3.8-Max
Input Cost Cost per million input tokens	$1.32 / 1M tokens	$2 / 1M tokens
Output Cost Cost per million tokens generated	$3.96 / 1M tokens	$6 / 1M tokens

Comparing Benchmarks and Performance

Compare the performances of DeepSeek's DeepSeek V4 Pro and Alibaba's Qwen3.8-Max on industry benchmarks. Scores are the ones the providers and public leaderboards report; a benchmark neither reports is left out.

	DeepSeek V4 Pro	Qwen3.8-Max
LMArena Elo Crowd-sourced blind preference rating on the LMArena text leaderboard.	Benchmark not available	1,481
GPQA Diamond Graduate-level science questions written to be search-proof.	90.1%	92.6%
SWE-bench Verified Resolving real GitHub issues end to end.	80.6%	Benchmark not available
SWE-bench Pro Harder, contamination-resistant successor of SWE-bench Verified; not comparable with it.	Benchmark not available	67.7%
MMLU-Pro Broad knowledge and reasoning across 14 subjects, harder successor of MMLU.	87.5%	Benchmark not available
HumanEval Functional correctness of generated code.	76.8%	Benchmark not available