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 | Qwen3 Coder Flashqwen3-coder-flash | Hy4 previewhy4-preview | GLM 5.3glm-5.3 |
|---|---|---|---|
| Pricing | |||
| Input | $0.30 / 1M | $0.834 / 1M | $1.40 / 1M |
| Output | $1.50 / 1M | $2.50 / 1M | $4.40 / 1M |
| Cache Write (5m) | $0.30 / 1M | $0.834 / 1M | $1.40 / 1M |
| Cache Write (1h) | $0.30 / 1M | $0.834 / 1M | $1.40 / 1M |
| Cache Read | $0.30 / 1M | $0.834 / 1M | $1.40 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 128K | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | No | Yes | No |
| Function Calling | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes |
| Catalogue | |||
| Provider | Alibaba | Tencent | Z.AI |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Qwen3 Coder Flash is Alibaba's fast, cost-efficient coding agent model — a lighter version of Qwen3 Coder Plus — built for autonomous programming through tool calling and environment interaction, while still retaining strong general-purpose abilities. | Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows. | GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution. |