Span-01 is a behavior scoring model from Respan. It reads a conversation span and returns, for each plain-language behavior you define, the probability that the behavior is present. It is suited for evaluation, guardrails, and monitoring of LLM and agent outputs at scale.
It is the higher-accuracy tier of the family. Span-01 Lite is the free, lighter tier.
Modalities
In / Out Price
$0.02 / $0per 1M
Released
Sep 26, 2026
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.
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. It runs on the OpenRouter Decisions API rather than the OpenAI-compatible chat endpoint, so the request and response shapes below are specific to structured decisions — chat completions SDKs will not work with it.
| $0.02 | Free | 0.17s |
Latency
0.17s
P50, best provider
100.00%
99.91%
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.
Span-01 is a behavior scoring model from Respan. It reads a conversation span and returns, for each plain-language behavior you define, the probability that the behavior is present. It is suited for evaluation, guardrails, and monitoring of LLM and agent outputs at scale. It is the higher-accuracy tier of the family. Span-01 Lite is the free, lighter tier.
Span-01 costs $0.02/M input tokens and $0.00/M output tokens.
Span-01 accepts text as input and returns structured decisions.
Span-01 Lite is another text model from Respan.
Span-01 was released on September 26, 2026.