# 🔬 Z-Image Base Anime Finetuning – Full Technical Test Report Epoch 100 Evaluation This guide documents a complete testing and evaluation process of a Z-Image Base anime finetuning checkpoint, including training details, inference settings, prompt engineering findings, and sampler recommendations. All findings are based on real testing with Epoch 100 checkpoint. ------------------------------------------------------------ 🧠 TRAINING DETAILS ------------------------------------------------------------ Base Model: Z-Image Base (Tongyi-MAI, released Jan 27, 2026) Architecture: S3-DiT (Single-Stream Diffusion Transformer) Text Encoder: Qwen-based (bilingual EN/CN) Training Type: Checkpoint Finetuning (not LoRA) Epochs: 100 Steps: 68,830 Dataset Size: 1,375 Anime Images Tagging System: WD Tagger (Booru-style tags) Avg Tags/Image: ~47 tags Unique Tags: 4,834 Total Tag Count: 64,276 ------------------------------------------------------------ 📐 DATASET RESOLUTION DISTRIBUTION ------------------------------------------------------------ Resolution | Count | Ratio | Quality -------------|-------|---------|--------- 1344x1728 | 132 | 3:4 | ✅ Good 768x1086 | 95 | ~9:13 | ⚠️ Odd-Size 832x1216 | 47 | ~2:3 | ✅ SD-Standard 1152x1536 | 45 | 3:4 | ✅ Good 768x1084 | 36 | Odd | ⚠️ Odd-Size 768x1024 | 28 | 3:4 | ✅ Perfect 896x1152 | 22 | 7:9 | ✅ Good 1365x768 | 20 | ~16:9 | ↔️ Landscape 1248x1824 | 19 | ~2:3 | ✅ Good 768x768 | 19 | 1:1 | ✅ Standard ------------------------------------------------------------ 🏷 TOP 50 TRAINING TAGS ------------------------------------------------------------ 1. 1162x 1girl 2. 1034x looking_at_viewer 3. 1033x solo 4. 1001x breasts 5. 980x long_hair 6. 839x blush 7. 689x smile 8. 595x large_breasts 9. 529x long_sleeves 10. 520x closed_mouth 11. 466x open_mouth 12. 456x bare_shoulders 13. 426x hair_between_eyes 14. 422x shirt 15. 420x thighs 16. 417x blue_eyes 17. 380x cleavage 18. 376x medium_breasts 19. 370x short_hair 20. 354x hair_ornament 21. 344x black_hair 22. 340x collarbone 23. 328x dress 24. 327x simple_background 25. 317x jewelry 26. 308x holding 27. 299x indoors 28. 298x navel 29. 297x sitting 30. 285x outdoors 31. 284x standing 32. 282x gloves 33. 275x skirt 34. 270x very_long_hair 35. 269x jacket 36. 269x white_background 37. 268x animal_ears 38. 259x brown_hair 39. 253x blonde_hair 40. 236x thighhighs 41. 232x white_shirt 42. 225x red_eyes 43. 220x parted_lips 44. 219x multicolored_hair 45. 216x cowboy_shot 46. 214x bow 47. 214x sky 48. 214x sweat 49. 207x ribbon 50. 207x purple_eyes ------------------------------------------------------------ 🏷 TOP 50 TRAINING TAGS nsfw ------------------------------------------------------------ 1. 139x nipples 2. 120x nude 3. 117x uncensored 4. 111x pussy 5. 100x from_behind 6. 98x lying 7. 94x penis 8. 81x sex 9. 80x covered_nipples 10. 73x completely_nude 11. 72x bra 12. 70x sideboob 13. 67x ass_visible_through_thighs 14. 65x spread_legs 15. 64x vaginal 16. 61x pussy_juice 17. 60x testicles 18. 59x saliva 19. 57x cameltoe 20. 53x erection 21. 52x anus 22. 50x pov 23. 45x sex_from_behind 24. 44x sex_from_behind 25. 41x huge_breasts 26. 40x pubic_hair 27. 39x clothed_sex 28. 38x cum 29. 36x bottomless 30. 35x bent_over 31. 34x wet_clothes 32. 33x oral 33. 32x straddling 34. 31x no_bra 35. 31x breasts_apart 36. 30x ass_grab 37. 29x cum_in_pussy 38. 29x clitoris 39. 27x ahegao 40. 27x rolling_eyes 41. 26x yuri 42. 25x fellatio 43. 25x breasts_out 44. 24x underwear_only 45. 23x bdsm 46. 22x standing_sex 47. 22x cleft_of_venus 48. 22x doggystyle 49. 22x anal 50. 21x cum_overflow ------------------------------------------------------------ ⚙ INFERENCE SETTINGS – WHAT WORKS ------------------------------------------------------------ Recommended Setup: CFG: 4 – 6 (sweet spot confirmed) Steps: 30 – 40 Resolution: 768x1024 (primary) 832x1216 (more detail) ModelSamplingFlow: Shift 3.0 ← important CFG Normalization: NOT tested ------------------------------------------------------------ 🎛 SAMPLER & SCHEDULER RESULTS ------------------------------------------------------------ CONFIRMED WORKING (anime-style output): ✔ Euler Ancestral + Simple ✔ Euler Ancestral + Normal ✔ DPM++ 2M + Simple ✔ DPM++ 2M + Normal ✔ DPM++ 2M SDE + Simple ✔ DPM++ 3M SDE + Simple ✔ Res Multistep + Simple ✔ Res Multistep + Normal COMPLETELY BROKEN (unrecognizable output): ✘ All Karras variants ✘ All Exponential variants Notes: → DPM++ 2M SDE and DPM++ 3M SDE tend to produce more realistic-looking backgrounds → All 8 working samplers produce top quality results → Personal preference decides final choice ------------------------------------------------------------ 🧪 PROMPT ENGINEERING FINDINGS ------------------------------------------------------------ WD Tags (Booru-style): + Fast to write + Good character details + Good clothing recognition - Slightly flatter clothing textures - Less atmospheric backgrounds - Less "alive" feeling overall Fulltext English: + Richer clothing details and textures + Better atmospheric backgrounds + More dynamic and "alive" feeling + Utilizes Qwen encoder strength fully + Better scene composition - Slightly longer to write ------------------------------------------------------------ 🏆 WINNING PROMPT STRUCTURE – LAYERED FULLTEXT ------------------------------------------------------------ 1. Opening line – Subject + Style 2. Character details – Clothing + Features 3. Action + Pose 4. Foreground + immediate environment 5. Background description 6. Composition + Lighting + Meta ------------------------------------------------------------ 🚫 NEGATIVE PROMPT FINDINGS ------------------------------------------------------------ Rule: POSITIVE → Fulltext NEGATIVE → Short keyword tags ------------------------------------------------------------ 🔤 TEXT GENERATION CAPABILITY ------------------------------------------------------------ Status after finetuning: INTACT ✅ Tested: ✔ Comic book covers with title text ✔ "BLADE ZERO" title text ✔ "ANIME MONTHLY" magazine cover ✔ Issue numbers and dates Notes: → Large text works very well → Small text slightly blurry (base limitation) → Occasional spelling errors (base model behavior) ------------------------------------------------------------ ⚠ KNOWN LIMITATIONS ------------------------------------------------------------ Anatomy: → Extra fingers / malformed hands still occur → Floating limbs appear occasionally → Manageable with negative prompts → Known Z-Image Base issue, not training fault Style Consistency: → Base model produces anime style ~50% of the time → Finetuned model produces anime style consistently ✅ Details: → Best detail at CFG 5–6, Steps 35–40 → ModelSamplingFlow Shift 3.0 is essential → Without Shift results are noticeably worse ------------------------------------------------------------ 🚀 QUICK START SETTINGS ------------------------------------------------------------ Node: ModelSamplingFlow → Shift 3.0 Sampler: DPM++ 2M SDE or Euler Ancestral Scheduler: Simple CFG: 5 Steps: 35 Resolution: 768x1024 Prompt style: Layered Fulltext Negative: Short keyword tags