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 | Gemini 2.5 Flash Litegemini-2.5-flash-lite | GLM 5.3glm-5.3 | GPT-6 Astragpt-6-astra |
|---|---|---|---|
| Pricing | |||
| Input | $0.15 / 1M | $1.40 / 1M | $10.00 / 1M |
| Output | $0.60 / 1M | $4.40 / 1M | $50.00 / 1M |
| Cache Write (5m) | $0.15 / 1M | $1.40 / 1M | $10.00 / 1M |
| Cache Write (1h) | $0.15 / 1M | $1.40 / 1M | $10.00 / 1M |
| Cache Read | $0.15 / 1M | $1.40 / 1M | $10.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 1.0M | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | No | Yes |
| Function Calling | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes |
| Catalogue | |||
| Provider | Z.AI | OpenAI | |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Gemini 2.5 Flash-Lite is a smaller, low-latency model focused on speed and cost efficiency. It delivers faster generation and better benchmark performance than earlier Flash models. Thinking mode is off by default for maximum speed, but developers can enable it when they want deeper reasoning at a higher cost. | 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-6 Astra is OpenAI's flagship model for demanding end-to-end professional work, designed for advanced analysis, software engineering, deep research, scientific tasks, and document creation. It is particularly strong in long-horizon agentic workflows, including tasks that require sustained reasoning, tool orchestration, and computer and browser use, making it well suited for complex autonomous workflows and production-grade knowledge work. |