Feature Extraction
MLX
Safetensors
qwen3
apple-silicon
quantized
mixed-precision
axquant
axq
development
8bit
8-bit precision
embedding
sentence-similarity
6-bit
Instructions to use AutomatosX/AX-Qwen3-Embedding-8B-MLX-AXQ-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Qwen3-Embedding-8B-MLX-AXQ-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir AX-Qwen3-Embedding-8B-MLX-AXQ-8bit AutomatosX/AX-Qwen3-Embedding-8B-MLX-AXQ-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| { | |
| "analysis_sha256": "a54939a08faa07d6c7033336d863bc52e44631a24af35e4365cb8245c1a62a68", | |
| "architecture_profile": { | |
| "adapter_id": "qwen3-dense-v1", | |
| "config_model_type": "qwen3", | |
| "dense": true, | |
| "mtp_declared": false, | |
| "notes": [ | |
| "Qwen3 dense (model_type=qwen3), including Qwen3-Embedding retrieval models.", | |
| "Embedding checkpoints share the causal backbone layout; use embedding runtimes for retrieval quality — do not claim generative or MTP metrics." | |
| ], | |
| "optimization_scope": "text-path", | |
| "product_family": "qwen3", | |
| "support_level": "supported", | |
| "support_tier": "convertible", | |
| "text_layer_count": 36, | |
| "vision_present": false | |
| }, | |
| "assignments": [ | |
| { | |
| "bits": 8, | |
| "group_size": 64, | |
| "method": "affine", | |
| "metrics": { | |
| "cosine_distance": 0.0253125, | |
| "decode_latency_cost": 0.0, | |
| "hidden_state_error": 0.045000000000000005, | |
| "long_context_loss": 0.016875, | |
| "mtp_acceptance_loss": 0.0045000000000000005, | |
| "output_kl": 0.05625, | |
| "peak_memory_cost": 0.0, | |
| "prefill_latency_cost": 0.0, | |
| "task_loss_delta": 0.036562500000000005, | |
| "token_disagreement": 0.030937500000000003 | |
| }, | |
| "module_path": "model.embed_tokens", | |
| "outlier_strategy": "none", | |
| "parameters": 621219840, | |
| "predicted_loss": 0.0307125, | |
| "reason": "protected embedding policy", | |
| "role": "embedding", | |
| "scale_strategy": "group-affine", | |
| "strategy_metadata": { | |
| "selected_from_candidates": 3, | |
| "storage_bpw": 8.5 | |
| }, | |
| "tensor": "model.embed_tokens.weight" | |
| }, | |
| { | |
| "bits": 16, | |
| "group_size": null, | |
| "method": "bf16", | |
| "metrics": { | |
| "cosine_distance": 0.0, | |
| "decode_latency_cost": 0.0, | |
| "hidden_state_error": 0.0, | |
| "long_context_loss": 0.0, | |
| "mtp_acceptance_loss": 0.0, | |
| "output_kl": 0.0, | |
| "peak_memory_cost": 0.0, | |
| "prefill_latency_cost": 0.0, | |
| "task_loss_delta": 0.0, | |
| "token_disagreement": 0.0 | |
| }, | |
| "module_path": "model.layers.0.input_layernorm", | |
| "outlier_strategy": "none", | |
| "parameters": 4096, | |
| "predicted_loss": 0.0, | |
| "reason": "non-quantizable tensor preserved", | |
| "role": "norm", | |
| "scale_strategy": "none", | |
| "strategy_metadata": { | |
| "selected_from_candidates": 1, | |
| "storage_bpw": 16.0 | |
| }, | |
| "tensor": "model.layers.0.input_layernorm.weight" | |
| }, | |
| { | |
| "bits": 6, | |
| "group_size": 32, | |
| "method": "affine", | |
| "metrics": { | |
| "cosine_distance": 0.03579728079756897, | |
| "decode_latency_cost": 0.0, | |
| "hidden_state_error": 0.06363961030678929, | |
| "long_context_loss": 0.02386485386504598, | |
| "mtp_acceptance_loss": 0.006363961030678929, | |
| "output_kl": 0.0795495128834866, | |
| "peak_memory_cost": 0.0, | |
| "prefill_latency_cost": 0.0, | |
| "task_loss_delta": 0.051707183374266295, | |
| "token_disagreement": 0.043752232085917636 | |
| }, | |
| "module_path": "model.layers.0.mlp.down_proj", | |
| "outlier_strategy": "none", | |
| "parameters": 50331648, | |
| "predicted_loss": 0.04343403403438369, | |
| "reason": "selected by marginal quality gain per storage bit", | |
| "role": "mlp", | |
| "scale_strategy": "group-affine", | |
| "strategy_metadata": { | |
| "selected_from_candidates": 7, | |
| "storage_bpw": 7.0 | |
| }, | |
| "tensor": "model.layers.0.mlp.down_proj.weight" | |
| }, | |
| { | |
| "bits": 6, | |
| "group_size": 32, | |
| "method": "affine", | |
| "metrics": { | |
| "cosine_distance": 0.03579728079756897, | |
| "decode_latency_cost": 0.0, | |
| "hidden_state_error": 0.06363961030678929, | |
| "long_context_loss": 0.02386485386504598, | |
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| "output_kl": 0.0795495128834866, | |
| "peak_memory_cost": 0.0, | |
| "prefill_latency_cost": 0.0, | |
| "task_loss_delta": 0.051707183374266295, | |
| "token_disagreement": 0.043752232085917636 | |
| }, | |
| "module_path": "model.layers.0.mlp.gate_proj", | |
| "outlier_strategy": "none", | |
| "parameters": 50331648, | |
| "predicted_loss": 0.04343403403438369, | |
| "reason": "selected by marginal quality gain per storage bit", | |
| "role": "mlp", | |
| "scale_strategy": "group-affine", | |
| "strategy_metadata": { | |
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| "storage_bpw": 7.0 | |
| }, | |
| "tensor": "model.layers.0.mlp.gate_proj.weight" | |
| }, | |
| { | |
| "bits": 6, | |
| "group_size": 32, | |
| "method": "affine", | |
| "metrics": { | |
| "cosine_distance": 0.03579728079756897, | |
| "decode_latency_cost": 0.0, | |
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| "peak_memory_cost": 0.0, | |
| "prefill_latency_cost": 0.0, | |
| "task_loss_delta": 0.051707183374266295, | |
| "token_disagreement": 0.043752232085917636 | |
| }, | |
| "module_path": "model.layers.0.mlp.up_proj", | |
| "outlier_strategy": "none", | |
| "parameters": 50331648, | |
| "predicted_loss": 0.04343403403438369, | |
| "reason": "selected by marginal quality gain per storage bit", | |
| "role": "mlp", | |
| "scale_strategy": "group-affine", | |
| "strategy_metadata": { | |
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| }, | |
| "tensor": "model.layers.0.mlp.up_proj.weight" | |
| }, | |
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| "method": "bf16", | |
| "metrics": { | |
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| "prefill_latency_cost": 0.0, | |
| "task_loss_delta": 0.0, | |
| "token_disagreement": 0.0 | |
| }, | |
| "module_path": "model.layers.0.post_attention_layernorm", | |
| "outlier_strategy": "none", | |
| "parameters": 4096, | |
| "predicted_loss": 0.0, | |
| "reason": "non-quantizable tensor preserved", | |
| "role": "norm", | |
| "scale_strategy": "none", | |
| "strategy_metadata": { | |
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| }, | |
| "tensor": "model.layers.0.post_attention_layernorm.weight" | |
| }, | |
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| "task_loss_delta": 0.0, | |
| "token_disagreement": 0.0 | |
| }, | |
| "module_path": "model.layers.0.self_attn.k_norm", | |
| "outlier_strategy": "none", | |
| "parameters": 128, | |
| "predicted_loss": 0.0, | |
| "reason": "non-quantizable tensor preserved", | |
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| }, | |
| "tensor": "model.layers.0.self_attn.k_norm.weight" | |
| }, | |
| { | |
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| "group_size": 64, | |
| "method": "affine", | |
| "metrics": { | |
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| "decode_latency_cost": 0.0, | |
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| "token_disagreement": 0.02475 | |
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| "outlier_strategy": "none", | |
| "parameters": 16777216, | |
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| "reason": "selected by marginal quality gain per storage bit", | |
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| "scale_strategy": "group-affine", | |
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| "method": "bf16", | |
| "metrics": { | |
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| "module_path": "model.layers.0.self_attn.q_norm", | |
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| "predicted_loss": 0.0, | |
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| "role": "norm", | |
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| "storage_bpw": 16.0 | |
| }, | |
| "tensor": "model.layers.0.self_attn.q_norm.weight" | |
| }, | |
| { | |
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| "group_size": 64, | |
| "method": "affine", | |
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| "module_path": "model.layers.0.self_attn.q_proj", | |
| "outlier_strategy": "none", | |
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| "strategy_metadata": { | |
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| "storage_bpw": 8.5 | |
| }, | |
| "tensor": "model.layers.0.self_attn.q_proj.weight" | |
| }, | |
| { | |
| "bits": 8, | |
| "group_size": 64, | |
| "method": "affine", | |
| "metrics": { | |
| "cosine_distance": 0.02025, | |
| "decode_latency_cost": 0.0, | |
| "hidden_state_error": 0.036, | |
| "long_context_loss": 0.056249999999999994, | |
| "mtp_acceptance_loss": 0.0036, | |
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| "module_path": "model.layers.0.self_attn.v_proj", | |
| "outlier_strategy": "none", | |
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| "predicted_loss": 0.027989999999999998, | |
| "reason": "selected by marginal quality gain per storage bit", | |
| "role": "attention", | |
| "scale_strategy": "group-affine", | |
| "strategy_metadata": { | |
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| "storage_bpw": 8.5 | |
| }, | |
| "tensor": "model.layers.0.self_attn.v_proj.weight" | |
| }, | |
| { | |
| "bits": 16, | |
| "group_size": null, | |
| "method": "bf16", | |
| "metrics": { | |
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| "prefill_latency_cost": 0.0, | |
| "task_loss_delta": 0.0, | |
| "token_disagreement": 0.0 | |
| }, | |
| "module_path": "model.layers.1.input_layernorm", | |
| "outlier_strategy": "none", | |
| "parameters": 4096, | |
| "predicted_loss": 0.0, | |
| "reason": "non-quantizable tensor preserved", | |
| "role": "norm", | |
| "scale_strategy": "none", | |
| "strategy_metadata": { | |
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| "storage_bpw": 16.0 | |
| }, | |
| "tensor": "model.layers.1.input_layernorm.weight" | |
| }, | |
| { | |
| "bits": 6, | |
| "group_size": 32, | |
| "method": "affine", | |
| "metrics": { | |
| "cosine_distance": 0.03579728079756897, | |
| "decode_latency_cost": 0.0, | |
| "hidden_state_error": 0.06363961030678929, | |
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| }, | |
| "module_path": "model.layers.1.mlp.down_proj", | |
| "outlier_strategy": "none", | |
| "parameters": 50331648, | |
| "predicted_loss": 0.04343403403438369, | |
| "reason": "selected by marginal quality gain per storage bit", | |
| "role": "mlp", | |
| "scale_strategy": "group-affine", | |
| "strategy_metadata": { | |
| "selected_from_candidates": 7, | |
| "storage_bpw": 7.0 | |
| }, | |
| "tensor": "model.layers.1.mlp.down_proj.weight" | |
| }, | |
| { | |
| "bits": 6, | |
| "group_size": 32, | |
| "method": "affine", | |
| "metrics": { | |
| "cosine_distance": 0.03579728079756897, | |
| "decode_latency_cost": 0.0, | |
| "hidden_state_error": 0.06363961030678929, | |
| "long_context_loss": 0.02386485386504598, | |
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| "outlier_strategy": "none", | |
| "parameters": 50331648, | |
| "predicted_loss": 0.04343403403438369, | |
| "reason": "selected by marginal quality gain per storage bit", | |
| "role": "mlp", | |
| "scale_strategy": "group-affine", | |
| "strategy_metadata": { | |
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| "storage_bpw": 7.0 | |
| }, | |
| "tensor": "model.layers.1.mlp.gate_proj.weight" | |
| }, | |
| { | |
| "bits": 6, | |
| "group_size": 32, | |
| "method": "affine", | |
| "metrics": { | |
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| "token_disagreement": 0.043752232085917636 | |
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| "module_path": "model.layers.1.mlp.up_proj", | |
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| "role": "mlp", | |
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| "storage_bpw": 7.0 | |
| }, | |
| "tensor": "model.layers.1.mlp.up_proj.weight" | |
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| "method": "bf16", | |
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| "task_loss_delta": 0.0, | |
| "token_disagreement": 0.0 | |
| }, | |
| "module_path": "model.layers.1.post_attention_layernorm", | |
| "outlier_strategy": "none", | |
| "parameters": 4096, | |
| "predicted_loss": 0.0, | |
| "reason": "non-quantizable tensor preserved", | |
| "role": "norm", | |
| "scale_strategy": "none", | |
| "strategy_metadata": { | |
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| "storage_bpw": 16.0 | |
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| "module_path": "model.layers.1.self_attn.k_norm", | |
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| "predicted_loss": 0.0, | |
| "reason": "non-quantizable tensor preserved", | |
| "role": "norm", | |
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