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Discover how Google's Gemini 3.8 Flash and Alibaba's Qwen3.8-Max stack up against each other in this comprehensive comparison of two leading AI language models. Released in September 2026 and September 2026 respectively, these models represent significant advancements in artificial intelligence, with Gemini 3.8 Flash offering a 1,048,576-token context window and Qwen3.8-Max offering a 1,000,000-token context window.

Explore their capabilities, pricing, and performance metrics, with Gemini 3.8 Flash achieving 1,493 on LMArena Elo and Qwen3.8-Max scoring 1,481, making this comparison essential for developers and organizations seeking the right AI solution for their specific needs.

Models Overview

	Gemini 3.8 Flash	Qwen3.8-Max
Provider The company that provides the model.	Google	Alibaba
Context Length Maximum number of tokens the model can process	1.05M	1M
Maximum Output Maximum number of tokens the model can generate in one response	65.54K	131.07K
Release Date When the model was first released.	02-09-2026	02-09-2026
Knowledge Cutoff When the model's training data ends.	Unknown	Unknown
Open Source Whether the model weights are openly available.	FALSE	TRUE

Pricing Comparison

Compare the pricing of Google's Gemini 3.8 Flash 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.

	Gemini 3.8 Flash	Qwen3.8-Max
Input Cost Cost per million input tokens	$0.75 / 1M tokens	$2 / 1M tokens
Output Cost Cost per million tokens generated	$3.75 / 1M tokens	$6 / 1M tokens

Comparing Benchmarks and Performance

Compare the performances of Google's Gemini 3.8 Flash 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.

	Gemini 3.8 Flash	Qwen3.8-Max
LMArena Elo Crowd-sourced blind preference rating on the LMArena text leaderboard.	1,493	1,481
GPQA Diamond Graduate-level science questions written to be search-proof.	Benchmark not available	92.6%
SWE-bench Pro Harder, contamination-resistant successor of SWE-bench Verified; not comparable with it.	Benchmark not available	67.7%
Terminal-Bench 2.1 Agentic tasks completed in a real terminal.	89.4%	Benchmark not available