ToPo-ToPo/Qwen3.8-27B-mlx-bf16
MLX bf16 conversion of Qwen/Qwen3.8-27B for Apple Silicon (mlx-vlm).
Provenance (self-converted from official weights)
- Source:
Qwen/Qwen3.8-27B(license: apache-2.0) - Tool:
mlx-vlm 0.6.9—mlx_vlm.convert --hf-path Qwen/Qwen3.8-27B --mlx-path . --dtype bfloat16 - Effective: bfloat16 (unquantized)
- Architecture:
Qwen3_5ForConditionalGeneration(model_type: qwen3_5), 64 layers with 3:1 linear/full attention, vision tower included (333 vision tensors).
Validation
- Text and image input verified with
mlx_vlm.generate. - OpenAI-compatible gateway (local-llm-server):
text, image (data URI) and native tool calling (
finish_reason: tool_calls) all verified. - End-to-end agent runs (MCP tools, write → read → report) completed without errors.
Throughput and memory use depend on your hardware, so measure them on your own machine.
Note on MTP
The official checkpoint declares mtp_num_hidden_layers: 1, but the mlx-vlm qwen3_5
conversion does not carry the model.mtp.* weights. A drafter split from the official
bf16 checkpoint is published separately as
ToPo-ToPo/Qwen3.8-27B-MTP-bf16
(a 4bit variant is also available).
Usage
from mlx_vlm import load, generate
model, processor = load("ToPo-ToPo/Qwen3.8-27B-mlx-bf16")