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WaveCut/Qwen3.6-35B-A3B-REAM-160-ru-agent-mlx_8bit
Qwen3.6-35B-A3B-REAM-160-ru-agent-mlx_8bit is a machine learning model from WaveCut. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
MLX/VLM quantization of WaveCut/Qwen3.6-35B-A3B-REAM-160-ru-agent.
Downloads · 30 days
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.safetensors24.9 GB · 100%
How the weights are stored.
U3222.6B · 98%
From the Hugging Face model README
MLX/VLM quantization of
WaveCut/Qwen3.6-35B-A3B-REAM-160-ru-agent.
mlx-vlm and LM Studio MLX engine.yes.yes.0 keys; source has 19. Current mlx-vlm qwen3_5_moe sanitizer drops mtp.* keys, so MTP runtime support is not claimed..{
"profile": "VLM-8bit",
"convert_status": "converted",
"convert_reason": null,
"converter": "mlx_vlm.convert",
"source_model": "WaveCut/Qwen3.6-35B-A3B-REAM-160-ru-agent",
"source_revision": "c3b73b8aaf70e2340d9b16424741213b5743936d",
"output_format": "MLX safetensors with mlx-vlm processor files",
"quantization_summary": {
"present": true,
"global": {
"group_size": 64,
"bits": 8,
"mode": "affine"
},
"explicit_rule_count": 80,
"rules_by_bits_group_mode": [
{
"bits": "8",
"group_size": "64",
"mode": "affine",
"count": 80
}
],
"rules_by_path_class": {
"router_or_gate": 80
}
}
}
| check | result |
|---|---|
mlx_vlm.load | yes |
| text smoke | yes |
| image smoke | yes |
| video smoke | skipped unless supported by current runtime |
| LM Studio smoke | not tested yet |
{
"metric": "proxy_smoke_score_not_kl",
"kl_status": "not_computed",
"domain_scores": {
"ru": 0.7751475733057623,
"agent": 0.9,
"code": 0.65,
"math": 0.8,
"vision": 0.8999999999999999
},
"weighted_score": 0.8325442719917286,
"text_kl": {
"status": "computed",
"summary": {
"mean": 0.0008244836847097758,
"p95": 0.0025505936238914718,
"max": 0.003115440718829632,
"weighted_mean": 0.0008720117882856154,
"same_top": 1.0,
"domains": {
"agent": {
"mean": 7.906566406745696e-05,
"p95": 0.0001360272567580978,
"max": 0.00014235632261261344,
"count": 2,
"same_top": 1.0
},
"code": {
"mean": 0.000385318482585717,
"p95": 0.0007160460583691019,
"max": 0.0007527935667894781,
"count": 2,
"same_top": 1.0
},
"math": {
"mean": 0.0008301898196805269,
"p95": 0.0014344516705023123,
"max": 0.0015015918761491776,
"count": 2,
"same_top": 1.0
},
"ru": {
"mean": 0.0020033607725054026,
"p95": 0.0030042327241972086,
"max": 0.003115440718829632,
"count": 2,
"same_top": 1.0
}
}
}
},
"mmlu_pro_validation20": {
"status": "not_computed",
"dataset": null,
"split": null,
"sample_count": null,
"summary": null,
"method": null,
"official_leaderboard": false
},
"mmlu_pro_test1000": {
"status": "not_computed",
"dataset": null,
"split": null,
"sample_count": null,
"summary": null,
"method": null,
"official_leaderboard": false,
"complete": null
},
"comparison_note": "Ranking uses text KL as the primary quantization signal, adds 1000-question MMLU-Pro test as a quality tie-breaker when available, and falls back to proxy smoke quality when KL is unavailable.",
"comparison_row": {
"profile": "VLM-8bit",
"converted": true,
"convert_status": "converted",
"convert_reason": null,
"structural_ok": true,
"smoke_ok": true,
"quality_score": 0.8325442719917286,
"kl_status": "computed",
"kl_weighted_mean": 0.0008720117882856154,
"kl_mean": 0.0008244836847097758,
"same_top": 1.0,
"mmlu_pro_validation20_accuracy": null,
"mmlu_pro_validation20_mean_margin": null,
"mmlu_pro_test1000_accuracy": null,
"mmlu_pro_test1000_mean_margin": null,
"size_bytes": 24925132285,
"score": 3.266995
},
"lm_studio": {
"status": "not_computed",
"ok": null,
"text_chat_ok": null,
"image_chat_ok": null,
"mtp_status": null,
"note": null
}
}
WaveCut/Qwen3.6-35B-A3B-REAM-160-ru-agentc3b73b8aaf70e2340d9b16424741213b5743936dmanifests/tool_versions.json.manifests/profile-VLM-8bit.json.