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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.

  1. Gemini 4 ArgonGoogleRemove
  2. Qwen3 Next 80B A3B InstructAlibabaRemove
gemini-4-argon vs qwen3-next-80b-a3b-instruct
AttributeGemini 4 Argongemini-4-argonQwen3 Next 80B A3B Instructqwen3-next-80b-a3b-instruct
Pricing
Input$2.00 / 1M$0.10 / 1M
Output$10.00 / 1M$0.40 / 1M
Cache Write (5m)$2.00 / 1M$0.10 / 1M
Cache Write (1h)$2.00 / 1M$0.10 / 1M
Cache Read$2.00 / 1M$0.10 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M262.1K
Max outputN/AN/A
Capabilities
VisionYesNo
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderGoogleAlibaba
Categorychatchat
Charge typePay As You GoPay As You Go
Released——
Description
SummaryGemini 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.Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model optimized for fast, stable answers without exposing chain-of-thought. It handles complex reasoning, code generation, knowledge QA, and multilingual tasks with strong alignment and formatting reliability. Designed for high throughput and stability on ultra-long inputs and multi-turn conversations, it’s well suited for RAG, tool use, and agent workflows where consistent final outputs matter. It delivers near–large-model performance with efficient inference, making it a strong choice for production assistants and long-context problem solving.