Files
hermes-agent/hermes_cli/local_runtime/catalog.json
emozilla b361fadd49 feat(local-runtime): derive the recommended model from memory size and bandwidth
The static recommended flag in catalog.json picked the dense 27B on
every machine, including unified-memory boxes where it decodes at
~13 tok/s while the 35B-A3B MoE does ~60. Replace the flag with a
per-machine derivation: decode is memory-bound, so predicted speed is
bandwidth over bytes-read-per-token, and the pick is the highest-quality
entry that runs resident and clears a 20 tok/s pleasant floor — else the
fastest resident entry, else the least-painful spill.

Catalog entries carry two authored fields in place of the flag:
quality (AA-informed ordering, editorially owned — never fetched at
runtime) and decode_fraction (share of weight bytes a token actually
reads; 1.0 dense, the active-slice ratio for MoE). The bandwidth axis
is the existing uma flag for now; measured per-machine bandwidth can
replace the class constants without touching the rule.

All three consumers derive: the pane badge and hero card through the
catalog route, quickstart's default target through the same resolver,
each gated on engine eligibility. The decision table lives on as a
checked-in test pinning every memory-class x bandwidth cell — a catalog
change flips cells in that file and the diff in review IS the editorial
sign-off. scripts/aa_quality_sync.py proposes quality updates at
authoring time; the commit decides.

The quickstart fixture's select_variant stub now constructs a real
VariantChoice — the resolver reads zero_spill, which the SimpleNamespace
stub lacked.
2026-08-29 22:38:40 -04:00

175 lines
4.8 KiB
JSON

{
"schema_version": 1,
"models": [
{
"id": "qwen3.8-27b",
"display_name": "Qwen3.8 27B",
"description": "Best all-round agent model; sees images; long context stays fast",
"repo": "unsloth/Qwen3.8-27B-GGUF",
"variants": [
{
"quant": "UD-Q4_K_M",
"files": [
{
"path": "Qwen3.8-27B-UD-Q4_K_M.gguf",
"size_bytes": 16464440224
}
]
}
],
"n_ctx_train": 262144,
"full_layers": 16,
"recurrent_layers": 48,
"per_layer_f16": 4096,
"n_vocab": 248320,
"mmproj": {
"path": "mmproj-BF16.gguf",
"size_bytes": 931146432,
"local": "mmproj-Qwen3.8-27B-BF16.gguf"
},
"mtp": true,
"mtp_draft_depth": 2,
"sampling": {
"temp": "1.0",
"top-p": "0.95",
"top-k": "20",
"min-p": "0.0"
},
"quality": 90,
"decode_fraction": 1.0
},
{
"id": "qwen3.8-flash-next",
"display_name": "Qwen3.8 Flash Next",
"description": "Frontier-scale model; needs a very large GPU to run well",
"repo": "unsloth/Qwen3.8-Flash-Next-GGUF",
"variants": [
{
"quant": "UD-Q4_K_XL",
"files": [
{
"path": "UD-Q4_K_XL/Qwen3.8-Flash-Next-UD-Q4_K_XL-00001-of-00004.gguf",
"size_bytes": 10946624
},
{
"path": "UD-Q4_K_XL/Qwen3.8-Flash-Next-UD-Q4_K_XL-00002-of-00004.gguf",
"size_bytes": 49859583136
},
{
"path": "UD-Q4_K_XL/Qwen3.8-Flash-Next-UD-Q4_K_XL-00003-of-00004.gguf",
"size_bytes": 49376141504
},
{
"path": "UD-Q4_K_XL/Qwen3.8-Flash-Next-UD-Q4_K_XL-00004-of-00004.gguf",
"size_bytes": 12087983520
}
]
}
],
"n_ctx_train": 262144,
"full_layers": 12,
"recurrent_layers": 36,
"per_layer_f16": 2048,
"moe": true,
"n_vocab": 248320,
"mmproj": {
"path": "mmproj-BF16.gguf",
"size_bytes": 907542944,
"local": "mmproj-Qwen3.8-Flash-Next-BF16.gguf"
},
"min_engine": "b10678",
"quality": 95,
"decode_fraction": 0.08
},
{
"id": "qwen3.6-35b-a3b",
"display_name": "Qwen3.6 35B-A3B",
"description": "Bigger mixture-of-experts with multi-token prediction; sees images",
"repo": "unsloth/Qwen3.6-35B-A3B-MTP-GGUF",
"variants": [
{
"quant": "UD-Q4_K_M",
"files": [
{
"path": "Qwen3.6-35B-A3B-UD-Q4_K_M.gguf",
"size_bytes": 22663387424
}
],
"validated": true
}
],
"n_ctx_train": 262144,
"full_layers": 10,
"recurrent_layers": 30,
"per_layer_f16": 2048,
"moe": true,
"mtp": true,
"n_vocab": 248320,
"mtp_draft_depth": 2,
"mmproj": {
"path": "mmproj-BF16.gguf",
"size_bytes": 902822528,
"local": "mmproj-Qwen3.6-35B-A3B-BF16.gguf"
},
"sampling": {
"temp": "1.0",
"top-p": "0.95",
"top-k": "20",
"min-p": "0.0"
},
"quality": 80,
"decode_fraction": 0.15
},
{
"id": "deepseek-v4-flash",
"display_name": "DeepSeek V4 Flash",
"description": "Frontier-class model for machines with 128GB+ memory",
"repo": "unsloth/DeepSeek-V4-Flash-0731-GGUF",
"variants": [
{
"quant": "UD-Q4_K_XL",
"files": [
{
"path": "UD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00001-of-00005.gguf",
"size_bytes": 5257408
},
{
"path": "UD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00002-of-00005.gguf",
"size_bytes": 48935523072
},
{
"path": "UD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00003-of-00005.gguf",
"size_bytes": 48980787136
},
{
"path": "UD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00004-of-00005.gguf",
"size_bytes": 49999168416
},
{
"path": "UD-Q4_K_XL/DeepSeek-V4-Flash-0731-UD-Q4_K_XL-00005-of-00005.gguf",
"size_bytes": 7174505088
}
]
}
],
"n_ctx_train": 1048576,
"full_layers": 43,
"recurrent_layers": 0,
"per_layer_f16": 1152,
"moe": true,
"n_vocab": 163840,
"draft": {
"path": "dspark-DeepSeek-V4-Flash-0731-Q8_0.gguf",
"size_bytes": 10896057440
},
"sampling": {
"temp": "1.0",
"top-p": "0.95",
"min-p": "0.01"
},
"quality": 85,
"decode_fraction": 0.1
}
]
}