diff --git a/README.md b/README.md
index a0b398b..3266f1d 100644
--- a/README.md
+++ b/README.md
@@ -138,8 +138,16 @@ The pre-trained public models use `--model-id 1` (R=9) and `--model-id 4` (R=13)
 After training (or starting from the shipped `.safetensors` files), you can export the model to
 ONNX and optionally apply INT8 or FP8 post-training quantization for deployment.
 
-Set the `ONNX_WORKFLOW` and (optionally) `QUANT_FORMAT` environment variables before running
-inference with `local_run.sh`:
+You may also change the surface code distance and number of rounds at inference
+time. That is - you are not required retrain a new model when changing either
+one of these parameters; since the model is a 3D convolutional neural network,
+the model will simply be run over a new decoding volume.
+
+- To run with a new distance, simply add `DISTANCE=<your distance>` to the commands below.
+- To run with a new number of rounds, simply add `N_ROUNDS=<your number of rounds>` to the commands below.
+
+Set the `ONNX_WORKFLOW` and (optionally) (`QUANT_FORMAT`, `DISTANCE`,
+`N_ROUNDS`) environment variables before running inference with `local_run.sh`:
 
 | `ONNX_WORKFLOW` | Behavior |
 |---|---|
@@ -169,7 +177,16 @@ ONNX_WORKFLOW=3 WORKFLOW=inference bash code/scripts/local_run.sh
 | `QUANT_FORMAT` | unset | `int8` or `fp8`. Unset means no quantization (FP32 ONNX). |
 | `QUANT_CALIB_SAMPLES` | `256` | Calibration samples for INT8/FP8 post-training quantization. |
 
+**Circuit variables:**
+
+| Variable | Default | Description |
+|---|---|---|
+| `CONFIG_NAME` | `config_public` | Use the defaults from the `conf/$CONFIG_NAME.yaml` file |
+| `DISTANCE` | Use the distance specified in the `conf/$CONFIG_NAME.yaml` file | surface code distance |
+| `N_ROUNDS` | Calibration samples for INT8/FP8 post-training quantization. | number of rounds in memory experiment |
+
 Notes:
+
 - TensorRT workflows (`ONNX_WORKFLOW=2` or `3`) require `tensorrt` and `modelopt`.
 - FP8 quantization failure is fatal. INT8 failure falls back to the FP32 ONNX model silently.
 - ONNX and engine files are written to the current working directory.
@@ -215,7 +232,7 @@ Results are written to `outputs/<EXPERIMENT_NAME>/plots/`.
 | Decoder | Source | Notes |
 |---|---|---|
 | No-op | — | Pre-decoder output only, no global correction |
-| Union-Find | `ldpc` | Fast, sub-optimal |
+| Union-Find | `ldpc` | Fast, sub-optimal LER (Logical Error Rate) |
 | BP-only | `ldpc` | Belief propagation, no OSD |
 | BP+LSD-0 | `ldpc` | BP with localized statistics decoding |
 | Uncorr-PM | PyMatching | Uncorrelated minimum-weight perfect matching |