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 | Perceptron Mk1.5perceptron-mk1.5 | Gemini 3.1 Flash Lite Previewgemini-3.1-flash-lite-preview | GPT-6 Sol Progpt-6-sol-pro |
|---|---|---|---|
| Pricing | |||
| Input | $0.15 / 1M | $0.25 / 1M | $2.00 / 1M |
| Output | $1.50 / 1M | $1.50 / 1M | $10.00 / 1M |
| Cache Write (5m) | $0.15 / 1M | $0.25 / 1M | $2.00 / 1M |
| Cache Write (1h) | $0.15 / 1M | $0.25 / 1M | $2.00 / 1M |
| Cache Read | $0.15 / 1M | $0.25 / 1M | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 36.9K | 1.0M | 1.1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | No | Yes | Yes |
| Function Calling | No | Yes | Yes |
| JSON Mode | No | Yes | Yes |
| Streaming | Yes | Yes | Yes |
| Catalogue | |||
| Provider | 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 | Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token. | Gemini 3.1 Flash Lite Preview is Google's high-efficiency model designed for high-volume and cost-sensitive workloads. It improves overall quality compared to Gemini 2.5 Flash Lite while approaching the performance of Gemini 2.5 Flash across key capabilities. The model delivers enhancements in audio input/ASR, RAG snippet ranking, translation, data extraction, and code completion, and supports configurable thinking levels (minimal, low, medium, high) for flexible cost–performance optimization. With pricing at roughly half the cost of Gemini 3 Flash, it is well suited for large-scale production deployments. | GPT-6 Sol Pro uses the same underlying model as GPT-6 Sol, but runs with reasoning.mode set to pro for higher-quality responses on complex and demanding tasks. Optimized for deeper reasoning, greater accuracy, and more reliable multi-step execution, it is particularly well suited for agentic coding, long-horizon software engineering, professional analysis, and complex automated workflows where solution quality takes priority over latency and cost. |