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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
| Attribute | GPT-4o Mini Transcribegpt-4o-mini-transcribe | Gemini 4 Argongemini-4-argon |
|---|---|---|
| Pricing | ||
| Input | $0.625 / 1M | $2.00 / 1M |
| Output | $0.625 / 1M | $10.00 / 1M |
| Cache Write (5m) | Not applicable | $2.00 / 1M |
| Cache Write (1h) | Not applicable | $2.00 / 1M |
| Cache Read | Not applicable | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M |
| Context | ||
| Max context | 128K | 1M |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | No | Yes |
| Function Calling | No | Yes |
| JSON Mode | Yes | Yes |
| Streaming | No | Yes |
| Catalogue | ||
| Provider | OpenAI | |
| Category | voice | chat |
| Charge type | Pay As You Go | Pay As You Go |
| Released | — | — |
| Description | ||
| Summary | GPT-4o Mini Transcribe is a smaller, cost-efficient speech-to-text model built on GPT-4o Mini's audio capabilities. It is designed for high-volume transcription workloads, delivering reliable performance with lower cost and latency. Priced per token (input and output), it provides transparent, fine-grained billing, making it well suited for scalable transcription pipelines, real-time applications, and cost-sensitive deployments. | Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response. |