Side-by-side comparison
Voxtral Small 24B 2507 vs GPT-4
Mistral
Voxtral Small 24B 2507
🔧 Tools
{} JSON
Input / 1M
$0.1000
Output / 1M
$0.3000
| Voxtral Small 24B 2507 | GPT-4 | |
|---|---|---|
| Provider | Mistral | OpenAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 32,000 | 8,191 |
| 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 → | 0.1000 | 30.0000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.3000 | 60.0000 |
Frequently asked questions
Which is cheaper, Voxtral Small 24B 2507 or GPT-4?
Voxtral Small 24B 2507 is cheaper than GPT-4 on a 50/50 input/output blend by about $44.8 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Voxtral Small 24B 2507 or GPT-4?
Voxtral Small 24B 2507 has the larger context window at 32k tokens versus 8k tokens for GPT-4. That means Voxtral Small 24B 2507 can ingest about 3.9x as much text per request.
What is the difference between Voxtral Small 24B 2507 and GPT-4?
Voxtral Small 24B 2507 comes from Mistral; GPT-4 comes from OpenAI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.