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 | GLM 5.3glm-5.3 | GPT-4o Audio Previewgpt-4o-audio-preview | Gemini 3.8 Flashgemini-3.8-flash |
|---|---|---|---|
| Pricing | |||
| Input | $1.40 / 1M | $0.875 / 1M | $0.75 / 1M |
| Output | $4.40 / 1M | $3.50 / 1M | $3.75 / 1M |
| Cache Write (5m) | $1.40 / 1M | Not applicable | $0.75 / 1M |
| Cache Write (1h) | $1.40 / 1M | Not applicable | $0.75 / 1M |
| Cache Read | $1.40 / 1M | Not applicable | $0.75 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 1M | 128K | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | No | No | Yes |
| Function Calling | Yes | No | Yes |
| JSON Mode | Yes | No | Yes |
| Streaming | Yes | Yes | Yes |
| Catalogue | |||
| Provider | Z.AI | OpenAI | |
| Category | chat | voice | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | 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. | gpt-4o-audio-preview adds support for audio inputs, allowing the model to understand nuances in audio recordings and enrich responses. It currently does not generate audio outputs, and audio input is billed per million audio tokens. | Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality. |