Llama 4 Maverick vs o1-pro
Llama 4 Maverick
| Llama 4 Maverick | o1-pro | |
|---|---|---|
| Provider | Meta | OpenAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary β | 1,048,576 | 200,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, json_mode | vision, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary β | 0.1500 | 150.0000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3β5Γ pricier than input. Glossary β | 0.6000 | 600.0000 |
Frequently asked questions
Which is cheaper, Llama 4 Maverick or o1-pro?
Llama 4 Maverick is cheaper than o1-pro on a 50/50 input/output blend by about $374.625 per 1M tokens. Exact savings depend on your input-vs-output ratio β use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Llama 4 Maverick or o1-pro?
Llama 4 Maverick has the larger context window at 1M tokens versus 200k tokens for o1-pro. That means Llama 4 Maverick can ingest about 5.2x as much text per request.
What is the difference between Llama 4 Maverick and o1-pro?
Llama 4 Maverick comes from Meta; o1-pro comes from OpenAI. They differ in pricing, context window, and supported capabilities β see the side-by-side table on this page for the exact figures, refreshed nightly.