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| Attribute | Qwen3.6-35B-A3Bqwen3.6-35b-a3b | Gemini 4 Argongemini-4-argon |
|---|---|---|
| Pricing | ||
| Input | $5.40 / 1M | $2.00 / 1M |
| Output | $32.40 / 1M | $10.00 / 1M |
| Cache Write (5m) | $5.40 / 1M | $2.00 / 1M |
| Cache Write (1h) | $5.40 / 1M | $2.00 / 1M |
| Cache Read | $5.40 / 1M | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M |
| Context | ||
| Max context | 262.1K | 1M |
| 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 | Qwen3.6-35B-A3B is an open-weight Mixture-of-Experts (MoE) multimodal model designed for agentic coding and long-horizon workflows. It features ~35–36B total parameters with ~3B activated per token, enabling strong performance with high inference efficiency. The model supports text and image inputs with a ~260K token context window, and is optimized for repository-level reasoning, multi-step development, and tool-driven workflows. With strong benchmark performance and improved coherence across extended tasks, Qwen3.6-35B-A3B is well suited for developer tools, coding agents, and real-world engineering applications that require both reasoning depth and efficiency. | 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. |