audit-reports / king.json
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king.json -> 5HTERMEJ…t3qJmnWf val_bpb 1.023364
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{
"schema_version": 2,
"as_of": "2026-07-09T09:20:12Z",
"network": {
"name": "mainnet",
"netuid": 40,
"label": "Bittensor mainnet · netuid 40",
"live": true
},
"current_king": {
"recipe_tag": "maxmfu-canonical",
"miner_hotkey": "5HTERMEJg8W2g6gi8vbmCaM1r6AGxujrji8iaQQLt3qJmnWf",
"miner_short": "5HTERMEJ…t3qJmnWf",
"miner_github": "star-dust9023",
"team_miner": false,
"bundle_hash": "6ec294cb748279ac0a2b848e934d3f54f5952d7205ee9a67d6f8ec558f59fd74",
"val_bpb": 1.023364,
"benchmark_accuracy": 0.197333,
"compute_cost_h100h": 4.689332,
"quality_gain": 0.0,
"tier": "verified",
"crowned_at": "2026-07-07T07:56:39Z",
"crowned_block": 8567947,
"hypothesis": "254M CANONICAL arch — king recipe (max_lr 0.003, WSD 0.55/0.45 1-sqrt, Muon) + embedding-LR split 0.009, determinism-off + torch.compile max-autotune for throughput. Genuine H200 run, real on-box calibration shipped. val_bpb ~1.025; validator op4 will measure the real number.",
"rationale_url": "https://github.com/RalphLabsAI/recipe/pull/1561"
},
"lineage": [
{
"recipe_tag": "v22_full_resub",
"miner_hotkey": "5DkeUCZNYrcGneX7wJDUqYxENX7CicSbzFhnbwhpyyDqYok6",
"miner_short": "5DkeUCZN…yyDqYok6",
"miner_github": "HadesHappy",
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"bundle_hash": "5569f7d8f66acddaab97cef7ed45f6b6fc66ee5088992718267c0a146c58aae1",
"val_bpb": 1.059665,
"benchmark_accuracy": 0.186,
"compute_cost_h100h": 4.815365807621729,
"quality_gain": 0.0,
"tier": "verified",
"crowned_at": "2026-07-06T01:02:59Z",
"crowned_block": 8558680,
"hypothesis": "In-place updates vs the pinned base: model/_v4skip.py (untied zero-init head + z-loss; checkpoint key-set identical to current canonical RalphBase), data/dataset.py (epoch-permutation no-replacement sampler), recipe/train.py (WSD stable/1-sqrt, Muon weight decay, embed AdamW, to…",
"rationale_url": "https://github.com/RalphLabsAI/recipe/pull/1408"
},
{
"recipe_tag": "crown10k_bb_b1",
"miner_hotkey": "5CXEMm6u6onoMpFPbpSqFLdeDzkG68nyTirSg3SVQfiMVhJa",
"miner_short": "5CXEMm6u…QfiMVhJa",
"miner_github": "danielortega-dev",
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"bundle_hash": "2725a3cab62346ec20022f79e752cd332fd5d8f2a550d06a1e64b2cc35b10033",
"val_bpb": 1.086352,
"benchmark_accuracy": 0.195333,
"compute_cost_h100h": 4.028397190132607,
"quality_gain": 0.0,
"tier": "verified",
"crowned_at": "2026-07-06T00:15:53Z",
"crowned_block": 8557322,
"hypothesis": "",
"rationale_url": "https://github.com/RalphLabsAI/recipe/pull/1271"
},
{
"recipe_tag": "eff5h-readout-v221",
"miner_hotkey": "5CqhtHE7BE8HgZTnCkhc7rWFSx5jzCQSsRYwhZtLfBBtLHkS",
"miner_short": "5CqhtHE7…fBBtLHkS",
"miner_github": "everettelages",
"team_miner": false,
"bundle_hash": "09caba0d5964ccc021acfa7561b5eba6b654c01bff0d9dd0068ee32cfa871c43",
"val_bpb": 1.301304,
"benchmark_accuracy": 0.198,
"compute_cost_h100h": 4.028397190132607,
"quality_gain": 0.0,
"tier": "verified",
"crowned_at": "2026-07-02T03:20:47Z",
"crowned_block": 8530602,
"hypothesis": "v0.2.21 readout-calibration arch (logit_scale + per-vocab readout_gain/readout_bias) on the 254M config — a genuinely trained 3800-step WSD run. Held-out val_bpb 1.3013, benchmark 0.198.",
"rationale_url": "https://github.com/RalphLabsAI/recipe/pull/865"
},
{
"recipe_tag": "run254c",
"miner_hotkey": "5HBQzPF5oEQ4nLXsYR3iTQ6mZintZp4xdtQLxgKCJgtEUbUt",
"miner_short": "5HBQzPF5…JgtEUbUt",
"miner_github": "martyniukr",
"team_miner": false,
"bundle_hash": "30971aef56998ffe09560ad73bd5208043c2d21c7f114f5b1803d24455ae727e",
"val_bpb": 1.31953,
"benchmark_accuracy": 0.184,
"compute_cost_h100h": 4.337059262283482,
"quality_gain": 0.0,
"tier": "verified",
"crowned_at": "2026-07-01T22:47:00Z",
"crowned_block": 8529235,
"hypothesis": "",
"rationale_url": "https://github.com/RalphLabsAI/recipe/pull/834"
},
{
"recipe_tag": "lr-h100proxy",
"miner_hotkey": "5DXfHZ3hegz4f924QqNwccqL4UuDQQS5GSY2jNj81aR6zPdE",
"miner_short": "5DXfHZ3h…1aR6zPdE",
"miner_github": "bravoou",
"team_miner": false,
"bundle_hash": "7fd43cef5ffcb2c7478483ef4408064158ddcd49b5a57287c1b740f57338a1b1",
"val_bpb": 1.375551,
"benchmark_accuracy": 0.964667,
"compute_cost_h100h": 3.42451352183573,
"quality_gain": 0.0,
"tier": "verified",
"crowned_at": "2026-06-30T02:56:47Z",
"crowned_block": 8516093,
"hypothesis": "Higher peak LR (max_lr 0.0008, king 6e-4) on the h100_proxy 254M config — a genuinely trained run. Held-out val_bpb 1.3756, benchmark 0.9647.",
"rationale_url": "https://github.com/RalphLabsAI/recipe/pull/595"
},
{
"recipe_tag": "batch-h100proxy",
"miner_hotkey": "5FCDTbBDka1WxcspxAjRMUeecp3vHnYiM1nenEsKGXysYqGE",
"miner_short": "5FCDTbBD…GXysYqGE",
"miner_github": "star-dust9023",
"team_miner": false,
"bundle_hash": "d93b5c601bf339ebee19528b3e457dcbded75e3ef15f448c0a9b6bf9c524ce9d",
"val_bpb": 3.974316,
"benchmark_accuracy": 0.202,
"compute_cost_h100h": 0.0,
"quality_gain": 0.0,
"tier": "verified",
"crowned_at": "2026-06-29T12:37:51Z",
"crowned_block": 8511879,
"hypothesis": "Scale the batch on the h100_proxy king config (recipe-v0.2.16, 254M): batch_size 512 (king 256), micro_batch_size 128 (king 64). A larger effective batch gives a smoother gradient estimate for the 254M model on H100; schedule, LR, and architecture unchanged. Held-out val_bpb 1.22, benchmark 0.972.",
"rationale_url": "https://github.com/RalphLabsAI/recipe/pull/553"
}
],
"meaningful_failures": [],
"stats": {
"total_kings": 7,
"current_val_bpb": 1.023364,
"current_benchmark": 0.197333
}
}