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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

Gemini 4 ArgonGoogle Remove
MiniMax M3MiniMax Remove

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Gemini 3.1 Flash Image (Google Vertex AI)Enterprise & partner access

gemini-4-argon vs minimax-m3
Attribute	Gemini 4 Argongemini-4-argon	MiniMax M3minimax-m3
Pricing
Input	$2.00 / 1M	$0.30 / 1M
Output	$10.00 / 1M	$1.20 / 1M
Cache Write (5m)	$2.00 / 1M	$0.30 / 1M
Cache Write (1h)	$2.00 / 1M	$0.30 / 1M
Cache Read	$2.00 / 1M	$0.30 / 1M
Web Search	$0 / 1M	$0 / 1M
Context
Max context	1M	1M
Max output	N/A	N/A
Capabilities
Vision	Yes	Yes
Function Calling	Yes	Yes
JSON Mode	Yes	Yes
Streaming	Yes	Yes
Catalogue
Provider	Google	MiniMax
Category	chat	chat
Charge type	Pay As You Go	Pay As You Go
Released	—	—
Description
Summary	Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.	MiniMax-M3 is a multimodal foundation model from MiniMax, supporting text, image, and video inputs with text output and a 1M-token context window. It is designed for long-horizon agentic workflows, coding, and tool-driven task execution, enabling sustained reasoning across complex tasks. Built on MiniMax Sparse Attention (MSA), the model dramatically improves long-context efficiency by replacing full attention with KV-block selection, reducing compute costs at 1M-token contexts while maintaining strong performance. Trained as a native multimodal model and optimized for multi-turn, production-style collaboration, MiniMax-M3 excels at extended, multi-step workflows rather than single-turn interactions.