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
- DeepSeek V4.1 FlashDeepSeekRemove
- DeepSeek V4 ProDeepSeekRemove
- Hy4 previewTencentRemove
4 is the maximum. Remove one to add another.
| Attribute | GLM 5.3 Flashglm-5.3-flash | DeepSeek V4.1 Flashdeepseek-v4.1-flash | DeepSeek V4 Prodeepseek-v4-pro | Hy4 previewhy4-preview |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0.075 / 1M | $0.30 / 1M | $0.435 / 1M | $0.834 / 1M |
| Output | $0.25 / 1M | $1.20 / 1M | $0.87 / 1M | $2.50 / 1M |
| Cache Write (5m) | $0.075 / 1M | $0.30 / 1M | $0.435 / 1M | $0.834 / 1M |
| Cache Write (1h) | $0.075 / 1M | $0.30 / 1M | $0.435 / 1M | $0.834 / 1M |
| Cache Read | $0.075 / 1M | $0.30 / 1M | $0.435 / 1M | $0.834 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 1M | 1M | 1.0M | 1M |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | Yes | Yes | Yes | Yes |
| Function Calling | Yes | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Z.AI | DeepSeek | DeepSeek | 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. | DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion. | DeepSeek V4 Pro is a large-scale Mixture-of-Experts (MoE) model with 1.6T total parameters and 49B activated per token, supporting a 1M-token context window for advanced reasoning and long-horizon workflows. It delivers strong performance across knowledge, mathematics, and software engineering tasks, making it suitable for complex, real-world applications. Built on a hybrid attention architecture for efficient long-context processing, the model supports configurable reasoning modes to balance speed and depth. It is well suited for full codebase analysis, multi-step automation, and large-scale information synthesis, where both capability and efficiency are essential.https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro | 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. |