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 | Universal-3.5 Prouniversal-3-5-pro | GLM 5 Turboglm-5-turbo | GPT-6.1 Solgpt-6.1-sol |
|---|---|---|---|
| Pricing | |||
| Input | — Not priced per input token | $0.96 / 1M | $2.00 / 1M |
| Output | — Not priced per output token | $3.20 / 1M | $10.00 / 1M |
| Cache Write (5m) | Not applicable | $0.96 / 1M | $2.00 / 1M |
| Cache Write (1h) | Not applicable | $0.96 / 1M | $2.00 / 1M |
| Cache Read | Not applicable | $0.96 / 1M | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | N/A | 202.8K | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | No | Yes | Yes |
| Function Calling | No | Yes | Yes |
| JSON Mode | No | Yes | Yes |
| Streaming | No | Yes | Yes |
| Catalogue | |||
| Provider | AssemblyAI | Z.AI | OpenAI |
| Category | voice | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | 2026-09-22 | — | — |
| Description | |||
| Summary | AssemblyAI Universal-3.5 Pro speech-to-text. Billed per second of audio. | GLM-5 Turbo is a high-performance model from Z.ai optimized for fast inference and agent-driven workflows. Designed for real-world environments such as OpenClaw scenarios, it delivers strong performance across long execution chains and complex task pipelines. The model features improved instruction decomposition, tool integration, scheduled and persistent execution, and enhanced stability for extended multi-step tasks, making it well suited for autonomous agents and production automation workflows. | GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical. |