Side-by-side comparison
GPT Audio vs Jamba Large 1.7
| GPT Audio | Jamba Large 1.7 | |
|---|---|---|
| Provider | OpenAI | AI21 |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 128,000 | 256,000 |
| 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 | 8.0000 |
Frequently asked questions
Which is cheaper, GPT Audio or Jamba Large 1.7?
Jamba Large 1.7 is cheaper than GPT Audio on a 50/50 input/output blend by about $1.25 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, GPT Audio or Jamba Large 1.7?
Jamba Large 1.7 has the larger context window at 256k tokens versus 128k tokens for GPT Audio. That means Jamba Large 1.7 can ingest about 2.0x as much text per request.
What is the difference between GPT Audio and Jamba Large 1.7?
GPT Audio comes from OpenAI; Jamba Large 1.7 comes from AI21. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.