Compare models
Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
| Attribute | Gemini 4 Argongemini-4-argon | Qwen3 Max Thinkingqwen3-max-thinking |
|---|---|---|
| Pricing | ||
| Input | $2.00 / 1M | $1.20 / 1M |
| Output | $10.00 / 1M | $6.00 / 1M |
| Cache Write (5m) | $2.00 / 1M | $1.20 / 1M |
| Cache Write (1h) | $2.00 / 1M | $1.20 / 1M |
| Cache Read | $2.00 / 1M | $1.20 / 1M |
| Web Search | $0 / 1M | $0 / 1M |
| Context | ||
| Max context | 1M | 262.1K |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | Yes | Yes |
| Function Calling | Yes | Yes |
| JSON Mode | Yes | Yes |
| Streaming | Yes | Yes |
| Catalogue | ||
| Provider | Alibaba | |
| 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. | Qwen3-Max-Thinking is the flagship reasoning model in the Qwen3 series, designed for high-stakes cognitive tasks that require deep, multi-step reasoning. By significantly scaling model capacity and reinforcement learning compute, it achieves substantial improvements in factual accuracy, complex reasoning, instruction following, alignment with human preferences, and agentic behavior. Optimized for advanced problem solving and long-horizon tasks, Qwen3-Max-Thinking is well suited for research, complex analysis, and agentic applications where reliability and structured reasoning are critical. |