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.
- GLM 5.3 FlashZ.AIRemove
- GLM 5.3Z.AIRemove
- Qwen2.5 Coder 7B InstructAlibabaRemove
- Hy4 previewTencentRemove
4 is the maximum. Remove one to add another.
| Attribute | GLM 5.3 Flashglm-5.3-flash | GLM 5.3glm-5.3 | Qwen2.5 Coder 7B Instructqwen2.5-coder-7b-instruct | Hy4 previewhy4-preview |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0.075 / 1M | $1.40 / 1M | $0.20 / 1M | $0.834 / 1M |
| Output | $0.25 / 1M | $4.40 / 1M | $0.20 / 1M | $2.50 / 1M |
| Cache Write (5m) | $0.075 / 1M | $1.40 / 1M | $0.20 / 1M | $0.834 / 1M |
| Cache Write (1h) | $0.075 / 1M | $1.40 / 1M | $0.20 / 1M | $0.834 / 1M |
| Cache Read | $0.075 / 1M | $1.40 / 1M | $0.20 / 1M | $0.834 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 1M | 1M | 32.8K | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | No | No | Yes |
| Function Calling | Yes | Yes | No | Yes |
| JSON Mode | Yes | Yes | No | Yes |
| Streaming | Yes | Yes | No | Yes |
| Catalogue | ||||
| Provider | Z.AI | Z.AI | Alibaba | Tencent |
| Category | chat | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — | — |
| Description | ||||
| Summary | GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads. | 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. | — | 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. |