| # SHADOW Assistant roadmap | |
| Every step from data to release. Updated 2026-10-31. | |
| **Overall: 16 of 46 steps done** `██████████░░░░░░░░░░░░░░░░░░░░` 35% | |
| | phase | progress | done | | |
| |---|---|---| | |
| | 1. [Data](#1-data) | `████████████████████` | 9 / 9 | | |
| | 2. [Proof and speed](#2-proof-and-speed) | `█████████████████░░░` | 5 / 6 | | |
| | 3. [Main pretraining](#3-main-pretraining) | `░░░░░░░░░░░░░░░░░░░░` | 0 / 5 | | |
| | 4. [Base benchmarks](#4-base-benchmarks) | `░░░░░░░░░░░░░░░░░░░░` | 0 / 6 | | |
| | 5. [Tuning (SFT)](#5-tuning-sft) | `░░░░░░░░░░░░░░░░░░░░` | 0 / 4 | | |
| | 6. [Final benchmarks](#6-final-benchmarks) | `░░░░░░░░░░░░░░░░░░░░` | 0 / 2 | | |
| | 7. [Runtimes and ports](#7-runtimes-and-ports) | `████░░░░░░░░░░░░░░░░` | 2 / 9 | | |
| | 8. [Release](#8-release) | `░░░░░░░░░░░░░░░░░░░░` | 0 / 5 | | |
| ## Now | |
| - ⏭️ next: **Main-run trainer** (window stages to 32k, anneal mix, skip lists, multi-GPU, streaming, resume) | |
| - ⏳ waiting: **Compute for the main run** (4x RTX PRO 6000, about 9 days) | |
| ## 1. Data | |
| | status | step | details | | |
| |---|---|---| | |
| | ✅ done | Text pretraining data | 286B tokens, 15 sources, Australian 34B | | |
| | ✅ done | Pictures and video | about 9.5B picture tokens, 256,874 ALA photos | | |
| | ✅ done | Audio | about 37,700 hours incl. WavCaps | | |
| | ✅ done | Anneal maths complete | about 10.7B tokens | | |
| | ✅ done | Tuning data | text 7.4M, vision 1.74M, audio 1.34M, Kimi 28,992 | | |
| | ✅ done | Final unigram prior | 285.7B tokens, 22,394 shards | | |
| | ✅ done | Benchmark skip lists | HellaSwag (3,299 videos), ESC-50/UrbanSound8K/VGGSound clips | | |
| | ✅ done | Pending sources closed | Trove declined; data final | | |
| | ✅ done | Public data card | README, GUIDE, AGENTS, decontamination lists | | |
| ## 2. Proof and speed | |
| | status | step | details | | |
| |---|---|---| | |
| | ✅ done | Archive proof | int4 KV, word-match search, best block last | | |
| | ✅ done | Full-size test run | 135M + 4B Engram, all senses, 0.85B tokens, passed | | |
| | ✅ done | Fetch on the trained model | fact recall 9% to 63% of digits | | |
| | ✅ done | Training speed kernels | fused GRU, fused readout, compile: 7.2x | | |
| | ✅ done | CPU speed up to 128k | 551 tok/s empty, 141 at 128k | | |
| | ⬜ to do | Training speed at 32k | on the main-run GPUs | | |
| ## 3. Main pretraining | |
| | status | step | details | | |
| |---|---|---| | |
| | ⏭️ next | Main-run trainer | window stages to 32k, anneal mix, skip lists, multi-GPU, streaming, resume | | |
| | ⏳ waiting | Compute for the main run | 4x RTX PRO 6000, about 9 days | | |
| | ⬜ to do | Text decontamination scan | 13-grams vs 9 benchmarks over all 286B tokens | | |
| | ⬜ to do | Pretraining, 2k to 12k | one pass of the corpus | | |
| | ⬜ to do | 32k stage and anneal | 40% long documents, 60% maths, code, best text | | |
| ## 4. Base benchmarks | |
| | status | step | details | | |
| |---|---|---| | |
| | ⬜ to do | Evaluation harness | runs every benchmark on each checkpoint | | |
| | ⬜ to do | Quality for the size | HellaSwag, ARC, PIQA, ArithMark, MMLU, GSM8K, code | | |
| | ⬜ to do | Window: 32k to 128k | needle in a haystack, RULER, YaRN to 128k | | |
| | ⬜ to do | Memory beyond the window | BABILong, LongMemEval, own archive test | | |
| | ⬜ to do | Pictures and video | MMMU, DocVQA, ChartQA, Video-MME, COCO | | |
| | ⬜ to do | Audio | LibriSpeech, AudioCaps, Clotho, MusicCaps, MMAU | | |
| ## 5. Tuning (SFT) | |
| | status | step | details | | |
| |---|---|---| | |
| | ⬜ to do | SFT trainer | chat template, loss on answers, Engram frozen | | |
| | ⬜ to do | Text SFT | 7.1M conversations | | |
| | ⬜ to do | Media SFT | pictures, video, sound and text together (SmolVLM2 mix) | | |
| | ⬜ to do | Kimi SFT | Australian life, identity, files, time, creative | | |
| ## 6. Final benchmarks | |
| | status | step | details | | |
| |---|---|---| | |
| | ⬜ to do | All benchmarks again | on the tuned model, plus IFEval | | |
| | ⬜ to do | Real-use demos | chat, photos, documents, sound, memory | | |
| ## 7. Runtimes and ports | |
| | status | step | details | | |
| |---|---|---| | |
| | ✅ done | CPU kernels at real size | ternary, int4 attention, RNN, Engram, eye | | |
| | ✅ done | Check which runtimes accept new models | llama.cpp takes new models (fork first, then pull requests); ONNX via a custom-op package; OpenVINO via optimum-intel | | |
| | ⬜ to do | C++ runtime with real weights | every feature, the speed headline | | |
| | ⬜ to do | Hugging Face model code | safetensors + modelling code; unblocks every converter | | |
| | ⬜ to do | llama.cpp fork, then pull requests | CPU text body first (TQ2_0, q4_0 KV), then GRU op, Engram, eye and ear; also reaches Ollama | | |
| | ⬜ to do | MLX (Apple) | single-file model, BitNet kernel exists | | |
| | ⬜ to do | ONNX custom-op package | stateful RNN, host code for Engram and archive | | |
| | ⬜ to do | OpenVINO | issue first with optimum-intel; Intel CPUs and GPUs | | |
| | ⬜ to do | Optional GPU path for eye and ear | about 20x faster sound encoding | | |
| ## 8. Release | |
| | status | step | details | | |
| |---|---|---| | |
| | ⬜ to do | Model on Hugging Face | weights, model card, CloudRift credit | | |
| | ⬜ to do | Public code repository | runtime and docs, one clean history | | |
| | ⬜ to do | Open SLM Leaderboard entry | sub-150M class | | |
| | ⬜ to do | Papers | paper 2: one space for all senses; index and archive | | |
| | ⬜ to do | Announce | after measured results | | |
| Status: ✅ done, 🔄 running, ⏭️ next, ⬜ to do, ⏳ waiting. | |