> For the complete documentation index, see [llms.txt](https://docs.inferix.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.inferix.io/inferix-whitepaper/economic-model/inferix-bench-and-ibme/ib-and-ibm.md).

# IB and IBM

Based on PoR, Inferix can assess the computing power of a Worker Node at a given time and uses a measurement unit called *Inferix Bench* (IB). When IB is multiplied by the node's working time, it results in *Inferix Bench minutes*, abbreviated as IBM. Thus, IBM is the metric used to measure the workload within the Inferix network.

To provide a quantitative perspective, 1 IB is defined as the average rendering capacity of a *standard unit node* with 2x RTX4090 GPUs, 32 GB of RAM, 1x Intel Core i9 CPU, SSD storage. This figure is updated daily using DAO mechanism, using benchmarks of a set of sample scenes on 10 nodes. The hardware specification of *standard unit nodes* and the *sample scenes* are also DAO-adjustable.

Assuming the average rendering time for one frame of a scene $$G$$ in the sample set is $$T^{0}*{G}$$, then it is not a fixed number, but is instead derived from the combined rendering capacity of the $$10$$ randomly selected *standard unit nodes* at the benchmarking time. The value of $$T^{0}*{G}$$ is influenced by GPU, CPU, storage read/write speeds and network speeds at the time of benchmarking, though the variation is negligible.

To determine the IB of any given node $$n$$, Inferix sends render requests for scene $$G$$ (randomly selected) to that node periodically. Assuming the average time it takes that node to render one frame in $$G$$ is $$T\_G$$, the rendering power of $$n$$ is defined by:

$$
\text{IB}\left(n\right) \triangleq \frac{T^{0}\_{G}}{T\_G}
$$

Thus, the larger the $$T\_G$$, the smaller the $$\text{IB}\_n$$ value.


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