Instructions to use TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit") config = load_config("TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Pi new
How to use TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit 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 "TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit"
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 TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit
Run Hermes
hermes
Darwin-35B-A3B-Opus
Quality: quantized (mixed quants per tensor, group size: 32, 9.191 bpw)
Most layers use 8-bit affine quantization with a group size 32, embeddings and some other layers are saved in bf16.
Model Specifications
| Architecture | Qwen3.5 MoE (Gated DeltaNet + MoE) |
| Total Parameters | 35B |
| Active Parameters | 3B per forward pass |
| Layers | 40 |
| Layout | 10 x (3 x GDN-MoE + 1 x Attention-MoE) |
| Experts | 256 (8 routed + 1 shared active) |
| Context Length | 262,144 native |
| Languages | 201 |
| Multimodal | Image and Video |
| License | Apache 2.0 |
Parent Models
Both parents share the identical Qwen3.5-35B-A3B architecture (40 layers, 256 experts, GDN+MoE hybrid). The Mother is a LoRA SFT on the same base — not a different architecture. "Text-only" refers to the training data (Claude 4.6 Opus reasoning chains), not the model structure.
| Role | Model | Architecture | Training |
|---|---|---|---|
| Father | Qwen/Qwen3.5-35B-A3B | Qwen3.5-35B-A3B | Original pre-training + RLHF |
| Mother | Jackrong/Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled | Qwen3.5-35B-A3B (same) | LoRA SFT with text-only Claude reasoning chains |
Source
This model was converted to MLX format from FINAL-Bench/Darwin-35B-A3B-Opus using mlx-vlm version 0.4.4.
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Model tree for TheCluster/Darwin-35B-A3B-Opus-MLX-mixed-9bit
Base model
FINAL-Bench/Darwin-35B-A3B-Opus