Energy table: whole-node estimate column (provisional x1.17); key facts point to the energy note

README.md

@@ -47,7 +47,7 @@ Built by [LogoLabs](https://logolabs.org), which makes AI logo generation.
 | **What** | Text-to-image, 512 × 512 (256 × 256 also supported), English prompts |
 | **Size** | 261M parameters with TAESD, 309.8M with SD-VAE: 192.1M active generator + 68.1M text encoder + decoder |
 | **Training** | From Agate's 256 px run (step 121,440), 24,900 more steps at 256 + 512 px; 196.6M images seen in the whole lineage |
-| **Compute** | 282.8 GH200-hours for the whole lineage from scratch (+22.5 for 512 px data preparation), 164.5 kWh, 4.94 kg CO₂e, measured with perun |
+| **Compute** | 282.8 GH200-hours for the whole lineage from scratch (+22.5 for 512 px data preparation), 164.5 kWh, 4.94 kg CO₂e; GPU energy measured with perun, see [About these energy figures](#compute-and-energy) |
 | **Qwen-Image-Bench** (1,000 prompts) | **32.6**. SD 1.5 29.1, Preview 002 28.9, Preview 001 28.2 |
 | **GenEval** (official) | **0.554**. Preview 002 0.577, 001 0.550; SDXL 0.55, SD 1.5 0.43 (published) |
 | **Speed** | 2.9 s per 512 px image on an RTX 4060 (50 steps, bf16, CUDA graphs; 4.5 s without), 5.7 GB peak VRAM |
@@ -281,36 +281,36 @@ Every GPU job was wrapped in [perun](https://github.com/Helmholtz-AI-Energy/peru
 of 1.3; CO₂e assumes 30 g/kWh (Swedish SE3 grid). Neither factor is confirmed by NAISS yet; seconds perun did not
 cover count at idle power, so the totals are a floor.
 
-| Run | Jobs | GH200-h | kWh | kg CO₂e |
-|---|---|---|---|---|
-| Latent cache (SD-VAE encode of the dataset) | 11 | 4.2 | 2.6 | 0.08 |
-| FCDM v1, epochs 1-10 | 2 | 13.7 | 8.7 | 0.26 |
-| FCDM v1, epochs 11-20 + Flan-T5 fine-tune | 1 | 20.6 | 13.5 | 0.41 |
-| DiT reproduction, epochs 1-10 | 1 | 13.1 | 8.8 | 0.26 |
-| fcdm2, all phases incl. restarts | 14 | 68.0 | 33.8 | 1.01 |
-| Run 1 thinker, epochs 1-10 | 1 | 19.0 | 12.6 | 0.38 |
-| T40r first try (diverged at step ~1,800) | 1 | 7.8 | 3.0 | 0.09 |
-| **T40r phase 1 (epochs 1-10)** | 1 | 47.3 | 27.7 | 0.83 |
-| **T40r phase 2 (joint Ettin training, to epoch 16)** | 1 | 37.1 | 18.8 | 0.56 |
-| **T40r caption phase (2 nodes, 8 h, cosine anneal)** | 1 | 60.3 | 35.2 | 1.06 |
-| T40r caption phase, two failed starts | 2 | 3.5 | 0.5 | 0.02 |
-| **cap2 continuation (003 branches at step 121,440)** | 1 | 61.0 | 35.9 | 1.08 |
-| **512 px: mr512_long1 (crashed; step 12,000 used)** | 1 | 19.6 | 12.5 | 0.37 |
-| **512 px: mr512_long2 (everything trainable)** | 1 | 21.5 | 12.0 | 0.36 |
-| **512 px: mr512_perc1 (perceptual + saliency)** | 1 | 72.4 | 43.8 | 1.31 |
-| 001 release benchmark and GenEval | 3 | 5.1 | 2.7 | 0.08 |
-| A/B wave 1 (six 256 px arms) + noise-scale study | 9 | 17.5 | 8.7 | 0.26 |
-| A/B wave 2 (does 512 px work?) | 2 | 12.1 | 6.7 | 0.20 |
-| A/B wave 2, failed attempts | 4 | 3.0 | 1.4 | 0.04 |
-| 512 px latents + saliency maps (data prep) | 21 | 22.5 | 14.7 | 0.44 |
-| Perceptual-loss profiling | 2 | 1.3 | 0.5 | 0.02 |
-| Perceptual-loss profiling, OOM | 2 | 0.6 | 0.1 | 0.00 |
-| Research after 003: logo LoRA, router, MoE pilots | 34 | 68.5 | 32.7 | 0.98 |
-| Evaluations, smoke tests, benchmarks | 47 | 30.9 | 11.7 | 0.35 |
-| **Whole Agate project to 2026-09-28** | 164 | **630.4** | **348.6** | **10.46** |
+| Run | Jobs | GH200-h | kWh | kg CO₂e | Whole-node est. (×1.17) |
+|---|---|---|---|---|---|
+| Latent cache (SD-VAE encode of the dataset) | 11 | 4.2 | 2.6 | 0.08 | 3.1 kWh / 0.09 kg |
+| FCDM v1, epochs 1-10 | 2 | 13.7 | 8.7 | 0.26 | 10.2 kWh / 0.31 kg |
+| FCDM v1, epochs 11-20 + Flan-T5 fine-tune | 1 | 20.6 | 13.5 | 0.41 | 15.8 kWh / 0.48 kg |
+| DiT reproduction, epochs 1-10 | 1 | 13.1 | 8.8 | 0.26 | 10.3 kWh / 0.31 kg |
+| fcdm2, all phases incl. restarts | 14 | 68.0 | 33.8 | 1.01 | 39.6 kWh / 1.19 kg |
+| Run 1 thinker, epochs 1-10 | 1 | 19.0 | 12.6 | 0.38 | 14.7 kWh / 0.44 kg |
+| T40r first try (diverged at step ~1,800) | 1 | 7.8 | 3.0 | 0.09 | 3.5 kWh / 0.10 kg |
+| **T40r phase 1 (epochs 1-10)** | 1 | 47.3 | 27.7 | 0.83 | 32.4 kWh / 0.97 kg |
+| **T40r phase 2 (joint Ettin training, to epoch 16)** | 1 | 37.1 | 18.8 | 0.56 | 22.0 kWh / 0.66 kg |
+| **T40r caption phase (2 nodes, 8 h, cosine anneal)** | 1 | 60.3 | 35.2 | 1.06 | 41.2 kWh / 1.24 kg |
+| T40r caption phase, two failed starts | 2 | 3.5 | 0.5 | 0.02 | 0.6 kWh / 0.02 kg |
+| **cap2 continuation (003 branches at step 121,440)** | 1 | 61.0 | 35.9 | 1.08 | 41.9 kWh / 1.26 kg |
+| **512 px: mr512_long1 (crashed; step 12,000 used)** | 1 | 19.6 | 12.5 | 0.37 | 14.6 kWh / 0.44 kg |
+| **512 px: mr512_long2 (everything trainable)** | 1 | 21.5 | 12.0 | 0.36 | 14.0 kWh / 0.42 kg |
+| **512 px: mr512_perc1 (perceptual + saliency)** | 1 | 72.4 | 43.8 | 1.31 | 51.3 kWh / 1.54 kg |
+| 001 release benchmark and GenEval | 3 | 5.1 | 2.7 | 0.08 | 3.1 kWh / 0.09 kg |
+| A/B wave 1 (six 256 px arms) + noise-scale study | 9 | 17.5 | 8.7 | 0.26 | 10.2 kWh / 0.31 kg |
+| A/B wave 2 (does 512 px work?) | 2 | 12.1 | 6.7 | 0.20 | 7.9 kWh / 0.24 kg |
+| A/B wave 2, failed attempts | 4 | 3.0 | 1.4 | 0.04 | 1.7 kWh / 0.05 kg |
+| 512 px latents + saliency maps (data prep) | 21 | 22.5 | 14.7 | 0.44 | 17.1 kWh / 0.51 kg |
+| Perceptual-loss profiling | 2 | 1.3 | 0.5 | 0.02 | 0.6 kWh / 0.02 kg |
+| Perceptual-loss profiling, OOM | 2 | 0.6 | 0.1 | 0.00 | 0.1 kWh / 0.00 kg |
+| Research after 003: logo LoRA, router, MoE pilots | 34 | 68.5 | 32.7 | 0.98 | 38.2 kWh / 1.15 kg |
+| Evaluations, smoke tests, benchmarks | 47 | 30.9 | 11.7 | 0.35 | 13.6 kWh / 0.41 kg |
+| **Whole Agate project to 2026-09-28** | 164 | **630.4** | **348.6** | **10.46** | **407.9 kWh / 12.24 kg** |
 
 Preview 003's own lineage, counted from scratch with jobs pro-rated at the steps where it branched off, cost
-**282.8 GH200-hours, 164.5 kWh and 4.94 kg CO₂e**, plus 22.5
+**282.8 GH200-hours, 164.5 kWh and 4.94 kg CO₂e** (whole-node est. 192.5 kWh / 5.78 kg), plus 22.5
 GH200-hours to encode the 512 px latents and saliency maps. The whole project to date cost 630.4 GPU-hours.
 
 **About these energy figures.** perun measured GPU power only, through NVML: on the GH200 superchip it does not