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 | GPT-4o Transcribegpt-4o-transcribe | Claude Fable 5.2claude-fable-5.2 | Gemini 4 Argongemini-4-argon |
|---|---|---|---|
| Pricing | |||
| Input | $1.25 / 1M | $8.00 / 1M | $2.00 / 1M |
| Output | — Not priced per output token | $40.00 / 1M | $10.00 / 1M |
| Cache Write (5m) | Not applicable | $10.00 / 1M | $2.00 / 1M |
| Cache Write (1h) | Not applicable | $16.00 / 1M | $2.00 / 1M |
| Cache Read | Not applicable | $0.20 / 1M | $2.00 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 128K | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | No | Yes | Yes |
| Function Calling | No | Yes | Yes |
| JSON Mode | Yes | Yes | Yes |
| Streaming | No | Yes | Yes |
| Catalogue | |||
| Provider | OpenAI | Anthropic | |
| Category | voice | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | GPT-4o Transcribe is OpenAI's high-quality speech-to-text model built on GPT-4o's audio capabilities. It delivers accurate transcription with strong language understanding, making it suitable for a wide range of audio processing tasks. Priced per token (input and output), it offers transparent, fine-grained billing, making it well suited for workflows that require scalable transcription, integration with LLM pipelines, and cost-aware processing. | Claude Fable 5.2 is Anthropic's most capable model for advanced technical work and open-ended problem solving, delivering significant improvements in coding, reasoning, and vision over Fable 5.1. It excels at exceptionally complex tasks, including large-scale software migrations, electronic system design, and advanced scientific and mathematical research. With up to 30% faster output generation, clearer communication, and always-on adaptive extended thinking, Fable 5.2 supports configurable reasoning effort from low to max (default high), with thinking preserved across turns. Designed for frontier engineering, scientific discovery, and ambitious long-horizon agentic workflows, it complements Opus 5.5 as a specialized option for the most demanding technical challenges. | 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. |