layer int64 2 23 | num_tokens int64 1k 1k | num_experts int64 32 32 | top_k int64 4 4 | stats dict | all_raw_logits listlengths 1k 1k | per_token listlengths 1k 1k |
|---|---|---|---|---|---|---|
2 | 1,000 | 32 | 4 | {"mean_top1_logit":0.8828,"std_top1_logit":0.4785,"mean_topk_logit":-0.0491,"std_logits":0.8086,"std(...TRUNCATED) | [[-2.265625,-1.8828125,-2.359375,-3.09375,-1.75,-2.21875,-3.15625,-2.15625,-3.515625,-2.703125,-1.92(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":-0.6133,"selected_experts":[21,25,18,14],"gate_weights":[0(...TRUNCATED) |
3 | 1,000 | 32 | 4 | {"mean_top1_logit":0.5273,"std_top1_logit":0.4766,"mean_topk_logit":-0.4629,"std_logits":0.7695,"std(...TRUNCATED) | [[-2.671875,-2.1875,-3.25,-2.578125,-2.609375,-0.275390625,-3.03125,-2.515625,-1.40625,-1.671875,-1.(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":-0.2754,"selected_experts":[5,29,30,10],"gate_weights":[0.(...TRUNCATED) |
4 | 1,000 | 32 | 4 | {"mean_top1_logit":0.6328,"std_top1_logit":0.7344,"mean_topk_logit":-0.4375,"std_logits":0.7734,"std(...TRUNCATED) | [[-1.8515625,-2.171875,-1.0390625,-1.078125,-2.234375,-2.15625,-1.4765625,-2.296875,-2.203125,-1.648(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":-0.7109,"selected_experts":[26,2,27,15],"gate_weights":[0.(...TRUNCATED) |
5 | 1,000 | 32 | 4 | {"mean_top1_logit":0.4297,"std_top1_logit":0.6016,"mean_topk_logit":-0.4004,"std_logits":0.7539,"std(...TRUNCATED) | [[-1.859375,-1.9375,-1.8359375,-1.4140625,-1.265625,-2.0625,-2.015625,-1.953125,-2.625,-2.75,-1.7734(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":-1.2109,"selected_experts":[17,29,3,4],"gate_weights":[0.2(...TRUNCATED) |
6 | 1,000 | 32 | 4 | {"mean_top1_logit":0.6133,"std_top1_logit":0.6172,"mean_topk_logit":-0.1709,"std_logits":0.7695,"std(...TRUNCATED) | [[-0.9140625,-3.703125,-0.43359375,-1.953125,0.4609375,-2.625,-1.484375,-2.375,-2.984375,-1.640625,-(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":0.4609,"selected_experts":[11,4,26,14],"gate_weights":[0.2(...TRUNCATED) |
7 | 1,000 | 32 | 4 | {"mean_top1_logit":0.4434,"std_top1_logit":0.6055,"mean_topk_logit":-0.4258,"std_logits":0.6992,"std(...TRUNCATED) | [[-2.140625,-2.1875,-1.3046875,-0.3125,-2.890625,-2.015625,-3.203125,-2.1875,-2.296875,-2.21875,-0.6(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":-0.3125,"selected_experts":[3,10,2,16],"gate_weights":[0.3(...TRUNCATED) |
8 | 1,000 | 32 | 4 | {"mean_top1_logit":0.4648,"std_top1_logit":0.543,"mean_topk_logit":-0.3652,"std_logits":0.7266,"std_(...TRUNCATED) | [[-2.4375,-0.8359375,-2.46875,-2.34375,-3.25,-2.515625,-2.75,-3.53125,-2.828125,-2.453125,-2.6875,-1(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":-0.8359,"selected_experts":[1,11,30,22],"gate_weights":[0.(...TRUNCATED) |
9 | 1,000 | 32 | 4 | {"mean_top1_logit":0.5,"std_top1_logit":0.5508,"mean_topk_logit":-0.2158,"std_logits":0.8398,"std_ga(...TRUNCATED) | [[-3.046875,-2.484375,-2.21875,-2.71875,-2.671875,-1.8828125,-2.015625,-1.390625,-2.03125,-2.421875,(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":-0.1943,"selected_experts":[17,11,21,7],"gate_weights":[0.(...TRUNCATED) |
10 | 1,000 | 32 | 4 | {"mean_top1_logit":0.5312,"std_top1_logit":0.5859,"mean_topk_logit":-0.1797,"std_logits":0.8203,"std(...TRUNCATED) | [[-0.67578125,-1.96875,0.609375,-1.5390625,-0.98046875,-1.5625,-1.359375,-1.4375,-1.640625,-1.9375,-(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":0.6094,"selected_experts":[2,30,0,21],"gate_weights":[0.37(...TRUNCATED) |
11 | 1,000 | 32 | 4 | {"mean_top1_logit":0.3809,"std_top1_logit":0.5898,"mean_topk_logit":-0.3477,"std_logits":0.7461,"std(...TRUNCATED) | [[-1.8125,-1.828125,-2.046875,-1.625,-1.59375,-2.640625,-2.015625,-1.828125,-2.15625,-3.0,-1.3515625(...TRUNCATED) | [{"token_idx":0,"token":"We","top1_logit":0.3496,"selected_experts":[26,11,20,14],"gate_weights":[0.(...TRUNCATED) |
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LFM2.5-8B-A1B Router Logit Analysis
Model: LiquidAI/LFM2.5-8B-A1B
Date: 2026-07-21T20:29:36.234301Z
Tokens processed: 1000
MoE layers analyzed: 22
Experts per layer: 32
Trained top-k: 4
Files
router_logits.json— Full per-token, per-layer data including ALL 32 raw logitsrouter_logits_raw.pt— PyTorch dict of raw logits tensors[N, 32]per layerrouter_summary.txt— Human-readable summary with statisticsREADME.md— This file
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