Overview
About this model
Model Overview Type: Causal Language Model with Vision Encoder Training Stage: Pre-training & Post-training Language Model Number of Parameters: 35B in total and 3B activated Hidden Dimension: 2048 Token Embedding: 248320 (Padded) Number of Layers: 40 Hidden Layout: 10 × (3 × (Gated DeltaNet → MoE) → 1 × (Gated Attention → MoE)) Gated DeltaNet: Number of Linear Attention Heads: 32 for V and 16 for QK Head Dimension: 128 Gated Attention: Number of Attention Heads: 16 for Q and 2 for KV Head Dimension: 256 Rotary Position Embedding Dimension: 64 Mixture Of Experts Number of Experts: 256 Number of Activated Experts: 8 Routed + 1 Shared Expert Intermediate Dimension: 512 LM Output: 248320 (Padded) MTP: trained with multi-steps Context Length: 262,144 natively and extensible up to 1,010,000 tokens.
Specifications
Model details
- Provider
- Alibaba
- Modality
- Vision
- Pricing
- $0.40 in · $0.40 out / 1M
API
Call it in code
One OpenAI-compatible API. Swap the model id and you're done.
from openai import OpenAI
client = OpenAI(
base_url="https://api.ecohash.com/v1",
api_key="YOUR_API_KEY",
)
response = client.chat.completions.create(
model="qwen3.5-35b-a3b",
messages=[{"role": "user", "content": [
{"type": "text", "text": "Describe this image"},
{"type": "image_url", "image_url": {"url": "..."}},
]}],
)More models
