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 | Grok 4.20 Multi-Agent Betagrok-4.20-multi-agent-beta | Perceptron Mk1.5perceptron-mk1.5 | GPT-6.1 Solgpt-6.1-sol |
|---|---|---|---|
| Pricing | |||
| Input | $2.00 / 1M | $0.15 / 1M | $2.00 / 1M |
| Output | $6.00 / 1M | $1.50 / 1M | $10.00 / 1M |
| Cache Write (5m) | $2.00 / 1M | $0.15 / 1M | $2.00 / 1M |
| Cache Write (1h) | $2.00 / 1M | $0.15 / 1M | $2.00 / 1M |
| Cache Read | $2.00 / 1M | $0.15 / 1M | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 2M | 36.9K | 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 | Yes | Yes |
| Catalogue | |||
| Provider | xAI | Perceptron | OpenAI |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | 2026-09-25 | — |
| Description | |||
| Summary | Grok 4.20 Multi-Agent Beta is a specialized variant of xAI's Grok 4.20 designed for collaborative, agent-based workflows. It enables multiple agents to operate in parallel, coordinating tool use and information synthesis to handle complex tasks. Optimized for deep research and multi-step problem solving, the model supports parallel reasoning, coordinated execution, and structured knowledge synthesis across large and complex workflows. | Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token. | 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. |