Side-by-side comparison
GPT Audio vs Mistral Large
| GPT Audio | Mistral Large | |
|---|---|---|
| Provider | OpenAI | Mistral |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 128,000 | 128,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools, json_mode | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 2.5000 | 2.0000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 10.0000 | 6.0000 |
Frequently asked questions
Which is cheaper, GPT Audio or Mistral Large?
Mistral Large is cheaper than GPT Audio on a 50/50 input/output blend by about $2.25 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
What is the difference between GPT Audio and Mistral Large?
GPT Audio comes from OpenAI; Mistral Large comes from Mistral. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.