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 | MiMo-V2-Omnimimo-v2-omni | Universal-3.5 Prouniversal-3-5-pro | GPT-6.1 Solgpt-6.1-sol |
|---|---|---|---|
| Pricing | |||
| Input | $0.40 / 1M | — Not priced per input token | $2.00 / 1M |
| Output | $2.00 / 1M | — Not priced per output token | $10.00 / 1M |
| Cache Write (5m) | $0.40 / 1M | Not applicable | $2.00 / 1M |
| Cache Write (1h) | $0.40 / 1M | Not applicable | $2.00 / 1M |
| Cache Read | $0.40 / 1M | Not applicable | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 262.1K | N/A | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | No | Yes |
| Function Calling | Yes | No | Yes |
| JSON Mode | Yes | No | Yes |
| Streaming | Yes | No | Yes |
| Catalogue | |||
| Provider | Xiaomi | AssemblyAI | OpenAI |
| Category | chat | voice | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | 2026-09-22 | — |
| Description | |||
| Summary | MiMo-V2-Omni is a frontier omni-modal model that natively processes image, video, and audio inputs within a unified architecture. It combines strong multimodal perception with advanced agentic capabilities, including visual grounding, multi-step planning, tool use, and code execution. With a 256K context window, MiMo-V2-Omni is well suited for complex real-world tasks that span multiple modalities, enabling integrated reasoning and execution across diverse input types. | AssemblyAI Universal-3.5 Pro speech-to-text. Billed per second of audio. | 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. |