diff --git a/cookbooks/cosmos3/generator/audiovisual/run_with_cosmos_framework.ipynb b/cookbooks/cosmos3/generator/audiovisual/run_with_cosmos_framework.ipynb
index 6d692701..456b911a 100644
--- a/cookbooks/cosmos3/generator/audiovisual/run_with_cosmos_framework.ipynb
+++ b/cookbooks/cosmos3/generator/audiovisual/run_with_cosmos_framework.ipynb
@@ -624,6 +624,85 @@
    "execution_count": null,
    "outputs": []
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Nano FP8: Text to Image\n",
+    "\n",
+    "FP8 checkpoints are published in the same Hugging Face repositories as the standard checkpoints, under the `fp8` revision rather than in separate FP8 repositories. This example downloads `nvidia/Cosmos3-Nano` at revision `fp8`. To use another released FP8 checkpoint, change `FP8_MODEL_ID` and `FP8_CHECKPOINT` below; keep `FP8_REVISION=fp8`.\n",
+    "\n",
+    "### Create Payload"
+   ],
+   "id": "fe1b922e"
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "source": [
+    "t2i_fp8_payload, t2i_fp8_output, t2i_fp8_model = create_payload(\"t2i\", backend=\"pytorch_fp8\")"
+   ],
+   "execution_count": null,
+   "outputs": [],
+   "id": "73ff907c"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Run"
+   ],
+   "id": "aaf87ed7"
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "source": [
+    "%%bash\n",
+    "set -euo pipefail\n",
+    "\n",
+    "cd \"$COSMOS3_REPO\"\n",
+    "FP8_MODEL_ID=\"nvidia/Cosmos3-Nano\"\n",
+    "FP8_REVISION=\"fp8\"\n",
+    "FP8_CHECKPOINT=\"$COSMOS3_REPO/checkpoints/Cosmos3-Nano-FP8\"\n",
+    "uvx hf@latest download \"$FP8_MODEL_ID\" \\\n",
+    "  --revision \"$FP8_REVISION\" \\\n",
+    "  --local-dir \"$FP8_CHECKPOINT\"\n",
+    "\n",
+    "CUDA_VISIBLE_DEVICES=\"$CUDA_VISIBLE_DEVICES\" LD_LIBRARY_PATH= \\\n",
+    "\"$COSMOS3_UV_ENV/bin/torchrun\" \\\n",
+    "  --nproc-per-node=\"$COSMOS3_NUM_GPUS\" \\\n",
+    "  --master-addr=\"$COSMOS3_MASTER_ADDR\" \\\n",
+    "  --master-port=\"$COSMOS3_TEXT_MASTER_PORT\" \\\n",
+    "  -m cosmos_framework.scripts.inference \\\n",
+    "  --parallelism-preset=throughput \\\n",
+    "  -i \"$COSMOS3_PYTORCH_FP8_T2I_INPUT\" \\\n",
+    "  -o \"$COSMOS3_PYTORCH_FP8_T2I_OUTPUT\" \\\n",
+    "  --checkpoint-path \"$FP8_CHECKPOINT\" \\\n",
+    "  --seed=0\n"
+   ],
+   "execution_count": null,
+   "outputs": [],
+   "id": "e0cbe358"
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### View Results"
+   ],
+   "id": "03e5c4b5"
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "source": [
+    "view_run(t2i_fp8_output)"
+   ],
+   "execution_count": null,
+   "outputs": [],
+   "id": "8970833a"
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/cookbooks/cosmos3/reasoner/run_with_cosmos_framework.ipynb b/cookbooks/cosmos3/reasoner/run_with_cosmos_framework.ipynb
index 55527d42..e156c18d 100644
--- a/cookbooks/cosmos3/reasoner/run_with_cosmos_framework.ipynb
+++ b/cookbooks/cosmos3/reasoner/run_with_cosmos_framework.ipynb
@@ -639,6 +639,82 @@
     "    print(json.dumps(json.loads(benchmark_path.read_text()).get(\"average\", {}), indent=2))\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "da7c0e0a",
+   "metadata": {},
+   "source": [
+    "### 7a. Optional: Run Nano FP8 Text Inference\n",
+    "\n",
+    "FP8 checkpoints are published in the same Hugging Face repositories as the standard checkpoints, under the `fp8` revision rather than in separate FP8 repositories. This example downloads `nvidia/Cosmos3-Nano` at revision `fp8`. To use another released FP8 checkpoint, change `FP8_MODEL_ID` and `FP8_CHECKPOINT` below; keep `FP8_REVISION=fp8`.\n",
+    "\n",
+    "Set `FP8_NUM_GPUS=1` to run without FSDP. To shard the model with FSDP, expose multiple GPUs in `CUDA_VISIBLE_DEVICES` and set `FP8_NUM_GPUS` to their count (for example, `CUDA_VISIBLE_DEVICES=0,1` and `FP8_NUM_GPUS=2`).\n",
+    "\n",
+    "Expected output file:\n",
+    "\n",
+    "```text\n",
+    "packages/cosmos3/outputs/cookbooks/cosmos3/reasoner/nano/cosmos_framework_nano_fp8_text/nano_text/reasoner_text.txt\n",
+    "```\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "228e450b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "set -euo pipefail\n",
+    "\n",
+    "cd \"$COSMOS3_REPO\"\n",
+    "FP8_MODEL_ID=\"nvidia/Cosmos3-Nano\"\n",
+    "FP8_REVISION=\"fp8\"\n",
+    "FP8_CHECKPOINT=\"$COSMOS3_REPO/checkpoints/Cosmos3-Nano-FP8\"\n",
+    "FP8_NUM_GPUS=\"${FP8_NUM_GPUS:-1}\"\n",
+    "uvx hf@latest download \"$FP8_MODEL_ID\" \\\n",
+    "  --revision \"$FP8_REVISION\" \\\n",
+    "  --local-dir \"$FP8_CHECKPOINT\"\n",
+    "\n",
+    "COSMOS_TRAINING=false CUDA_VISIBLE_DEVICES=\"$CUDA_VISIBLE_DEVICES\" \\\n",
+    ".venv/bin/torchrun \\\n",
+    "  --nproc-per-node=\"$FP8_NUM_GPUS\" \\\n",
+    "  --master-addr=\"$COSMOS3_MASTER_ADDR\" \\\n",
+    "  --master-port=\"$COSMOS3_NANO_TEXT_MASTER_PORT\" \\\n",
+    "  -m cosmos_framework.scripts.inference \\\n",
+    "  --parallelism-preset=throughput \\\n",
+    "  --dp-shard-size=\"$FP8_NUM_GPUS\" \\\n",
+    "  --dp-replicate-size=1 \\\n",
+    "  --cp-size=1 \\\n",
+    "  --cfgp-size=1 \\\n",
+    "  --no-use-torch-compile \\\n",
+    "  -i \"$COSMOS3_INPUT_DIR/nano_text.json\" \\\n",
+    "  -o \"$COSMOS3_OUTPUT_ROOT/cosmos_framework_nano_fp8_text\" \\\n",
+    "  --checkpoint-path \"$FP8_CHECKPOINT\" \\\n",
+    "  --seed=0 \\\n",
+    "  --benchmark\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7fdbcd0f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import os, json\n",
+    "\n",
+    "output_root = Path(os.environ[\"COSMOS3_OUTPUT_ROOT\"])\n",
+    "text_path = output_root / \"cosmos_framework_nano_fp8_text\" / \"nano_text\" / \"reasoner_text.txt\"\n",
+    "benchmark_path = output_root / \"cosmos_framework_nano_fp8_text\" / \"benchmark.json\"\n",
+    "\n",
+    "print(text_path)\n",
+    "print(text_path.read_text())\n",
+    "if benchmark_path.exists():\n",
+    "    print(json.dumps(json.loads(benchmark_path.read_text()).get(\"average\", {}), indent=2))\n"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "5e7b2393",