Text Generation
MLX
Safetensors
qwen3_5_moe
apple-silicon
quantized
mixed-precision
axquant
axq
stable-default-runtime
quality-validated
checkpoint-tier1
certified
qwen3.6
6bit
6-bit
v2
mtp
vision
conversational
4-bit precision
Instructions to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "AutomatosX/AX-Qwen3.6-35B-A3B-MLX-AXQ-6bit-MTP" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
| { | |
| "axquant_version": "1.2.0", | |
| "calibration": null, | |
| "created_at": "2026-08-05T13:39:34.268276Z", | |
| "effective_bpw": 5.999999959946398, | |
| "files": [ | |
| { | |
| "path": "README.md", | |
| "sha256": "6820fb1bcb278a7d44d17292849849fd2dff99b7f4ef3eec65b12a25dc2015f5", | |
| "size_bytes": 10309 | |
| }, | |
| { | |
| "path": "axquant_mtp_sidecar_manifest.json", | |
| "sha256": "c0f5463aa1557c67bd0adb7498e507c9dffe8de34aadc0f72a1fd86a3ba2bcf7", | |
| "size_bytes": 1066 | |
| }, | |
| { | |
| "path": "axquant_plan.json", | |
| "sha256": "07b6cecbf58a9f1c71814ba8b9050bf0aff2adec41ecc4a884e18629635b01cf", | |
| "size_bytes": 987594 | |
| }, | |
| { | |
| "path": "axquant_quantizer_execution.json", | |
| "sha256": "c164ccc95fcb87945b85399defcfd22dd132f7426cffd404ebf7533f22e855bb", | |
| "size_bytes": 124464 | |
| }, | |
| { | |
| "path": "axquant_runtime.json", | |
| "sha256": "4c7df1a009cc989f9dedd9113b377c88e52235e55dbd209b1ab5466eda033620", | |
| "size_bytes": 1676 | |
| }, | |
| { | |
| "path": "axquant_vision_sidecar_manifest.json", | |
| "sha256": "af9e491342387394a21292114a19b464357375314c30b1799b168d3120c1e84d", | |
| "size_bytes": 1072 | |
| }, | |
| { | |
| "path": "chat_template.jinja", | |
| "sha256": "e84f32a23fdda27689f868aa4a1a5621f41133e51a48d7f3efcbea2839574259", | |
| "size_bytes": 7764 | |
| }, | |
| { | |
| "path": "config.json", | |
| "sha256": "30898a68ce3c1dc40ef83ae9ca8606013e97e1a6e9281409c9351395e4ff03ba", | |
| "size_bytes": 138993 | |
| }, | |
| { | |
| "path": "generation_config.json", | |
| "sha256": "e70c136c1b78ddc1fb0905bac8e733a4dc448d4f852a5dd75143fffc70be550e", | |
| "size_bytes": 202 | |
| }, | |
| { | |
| "path": "model-00001-of-00005.safetensors", | |
| "sha256": "860f667408f32e2353c15e7f88efcb8882b5e93e73afc222cb29b9cdf3a89c44", | |
| "size_bytes": 5367600594 | |
| }, | |
| { | |
| "path": "model-00002-of-00005.safetensors", | |
| "sha256": "2dba4e082f746e20d94ee9623e5ba879379a1c2a9079bcf79a457df5b8856e29", | |
| "size_bytes": 5358260540 | |
| }, | |
| { | |
| "path": "model-00003-of-00005.safetensors", | |
| "sha256": "f6c517b13633c3c3455f8c1f05b7a804fa0e6bcecb091f61a2c7cb825436e8ba", | |
| "size_bytes": 5349479920 | |
| }, | |
| { | |
| "path": "model-00004-of-00005.safetensors", | |
| "sha256": "d2fbee3ba144584f68333788d2d31f0339a51d4aa6f0d5cbfdfd8c5260b0333c", | |
| "size_bytes": 5252632964 | |
| }, | |
| { | |
| "path": "model-00005-of-00005.safetensors", | |
| "sha256": "860cfe8a94c0b2d8ca4ab509545096e5af73b480724147e1ffc92e2ce02b0df0", | |
| "size_bytes": 3053704637 | |
| }, | |
| { | |
| "path": "model.safetensors.index.json", | |
| "sha256": "e2316c3702cf36cd3ed4a1ce3aa9cd507a3832944b3e8e99a1b10258da701e92", | |
| "size_bytes": 186677 | |
| }, | |
| { | |
| "path": "mtp.safetensors", | |
| "sha256": "ba25d917acc7ed17b0df9f3d16809b44478bf56c0de615020a39c7b09b961f77", | |
| "size_bytes": 1689283776 | |
| }, | |
| { | |
| "path": "mtplx_runtime.json", | |
| "sha256": "9f8e8c16ec3bbbcdc194127ed55a01bf8ca0490e4e961feaa7424d3a73b539a2", | |
| "size_bytes": 888 | |
| }, | |
| { | |
| "path": "tokenizer.json", | |
| "sha256": "06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523", | |
| "size_bytes": 19989325 | |
| }, | |
| { | |
| "path": "tokenizer_config.json", | |
| "sha256": "95c557768e6b88a7128befc7bfd3c7de50e5d51af9b8b33a9f4dee0e04f99679", | |
| "size_bytes": 1161 | |
| }, | |
| { | |
| "path": "vision.safetensors", | |
| "sha256": "6623410d69074faf0ea027f1c1c3cabd731bd70d5bcb3b878a595eaba4c17767", | |
| "size_bytes": 893179624 | |
| } | |
| ], | |
| "format": "mlx", | |
| "logical_parameters": 35951822704, | |
| "main_logical_parameters": 35107181936, | |
| "main_weight_file_size_bytes": 25274858279, | |
| "measured_main_bpw": 5.759472993321032, | |
| "measured_total_bpw": 6.000061199011191, | |
| "mtp_acceptance_retention": null, | |
| "mtp_distribution": { | |
| "bf16": { | |
| "fraction": 1.0, | |
| "parameters": 844640768 | |
| } | |
| }, | |
| "mtp_measured_speedup": null, | |
| "mtp_policy": { | |
| "candidate_bits": [ | |
| 8, | |
| 16 | |
| ], | |
| "min_bits": 8, | |
| "mode": "protected", | |
| "optimize_for_acceptance": true, | |
| "preserve_external_sidecar": true, | |
| "protect_norms": true, | |
| "protect_output_head": true | |
| }, | |
| "mtp_present": true, | |
| "mtp_weight_file_size_bytes": 1689283776, | |
| "plan_sha256": "b1f023ba3430624efdd56327af37b5b814d093e4b9a114788d5c1dcc1f88da3c", | |
| "profile": "general", | |
| "protected_weight_file_size_bytes": 893179624, | |
| "quantizer": "axquant", | |
| "runtime": { | |
| "ax_engine": { | |
| "decode_kernel": null, | |
| "fused_mtp": null, | |
| "kernel_evidence": "unmeasured", | |
| "model_manifest": "model-manifest.json", | |
| "preferred_group_size": 32 | |
| }, | |
| "compatible_runtimes": [ | |
| { | |
| "compatibility_level": "B", | |
| "manifest": "config.json", | |
| "mtp_support": "runtime-dependent", | |
| "name": "mlx-lm", | |
| "notes": [ | |
| "Standard backbone inference is the compatibility target.", | |
| "AXQuant MTP metadata may be ignored by MLX-LM." | |
| ], | |
| "standard_inference": true, | |
| "standard_mlx_weights": true, | |
| "support_level": "standard-inference" | |
| } | |
| ], | |
| "created_at": "2026-08-05T13:39:05.854633Z", | |
| "kv_cache": null, | |
| "memory_policy": { | |
| "kv_cache_precision": "runtime-default", | |
| "mtp_buffers": "preallocate-when-enabled", | |
| "prefix_cache": "runtime-managed", | |
| "unified_memory_safety_margin": "benchmark-required" | |
| }, | |
| "mtp": { | |
| "acceptance_retention": null, | |
| "detected": true, | |
| "draft_tokens": 1, | |
| "enabled_by_default": true, | |
| "head_precision": null, | |
| "measured_speedup": null, | |
| "optimized": false, | |
| "recommended_temperature_max": null, | |
| "sidecar_file": "mtp.safetensors", | |
| "verification_mode": "runtime-default" | |
| }, | |
| "optimization_scope": "text-path", | |
| "primary_runtime": { | |
| "compatibility_level": "A", | |
| "manifest": "model-manifest.json", | |
| "mtp_support": "native", | |
| "name": "ax-engine", | |
| "notes": [ | |
| "Runtime claims require a passing AX Engine doctor and benchmark report." | |
| ], | |
| "standard_inference": true, | |
| "standard_mlx_weights": true, | |
| "support_level": "optimized" | |
| }, | |
| "schema_version": "axquant.runtime.v1" | |
| }, | |
| "schema_version": "axquant.artifact.v2", | |
| "software_versions": { | |
| "ax_engine": null, | |
| "axquant": "1.2.0", | |
| "mlx": "0.32.0", | |
| "mlx_lm": "0.31.3", | |
| "pydantic": "2.13.4", | |
| "python": "3.13.14", | |
| "safetensors": "0.8.0" | |
| }, | |
| "source_model": { | |
| "architecture": "Qwen3_5MoeForConditionalGeneration", | |
| "format": "mlx", | |
| "local_path": null, | |
| "model_id": "Qwen/Qwen3.6-35B-A3B", | |
| "revision": "995ad96eacd98c81ed38be0c5b274b04031597b0" | |
| }, | |
| "target_class": "6bit", | |
| "weight_distribution": { | |
| "4bit": { | |
| "fraction": 0.6869209985632332, | |
| "parameters": 24696061952 | |
| }, | |
| "6bit": { | |
| "fraction": 0.2434625553220185, | |
| "parameters": 8752922624 | |
| }, | |
| "8bit": { | |
| "fraction": 0.019523428722346983, | |
| "parameters": 701902848 | |
| }, | |
| "bf16": { | |
| "fraction": 0.0500930173924013, | |
| "parameters": 1800935280 | |
| } | |
| }, | |
| "weight_file_size_bytes": 26964142055 | |
| } | |