The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought.
The o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the launch announcement(opens in new tab).
Modalities
In / Out Price
$15 / $60per 1M
Context
200K
Released
Dec 17, 2024
Knowledge Cutoff
Oct 2023
This model is hosted by one provider. OpenRouter forwards every request to it directly — no routing decisions to make.
The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows where this model lands among all models on OpenRouter.
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Token volume and request traffic to this model over time.
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.
The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. The o1 models are optimized for math, science, programming, and other STEM-related tasks.
o1 costs $15.00/M input tokens and $60.00/M output tokens, with separate rates for Cache Read at $7.50/M tokens.
o1 has a 200,000 token context window. It supports up to 100,000 completion tokens.
Yes. o1 accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
o1 accepts text, images and files such as PDFs as input and returns text.
GPT-5.6 Luna Pro, GPT-5.6 Luna, GPT-5.6 Terra Pro and 55 more are other text models from OpenAI.
o1 was released on December 17, 2024. Its knowledge cutoff is October 31, 2023.
| $15.00 | $60.00 | $7.50 | 2.88s | 34 tps |
Throughput
34tok/s
P50, best across providers
Latency
2.88s
P50, best provider
100.00%
100.00%
When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.