Qwen3.5-397B Model Technical and Cost Overview | Generated by AI
Question: What are the training details, architecture, and estimated costs for Qwen3.5-397B-A17B?
Answer: Released in February 2026, Qwen3.5-397B-A17B is a flagship native vision-language model from Alibaba’s Qwen team. It is notable for its massive scale combined with high inference efficiency due to its sparse architecture.
1. Model Architecture
The model uses a Hybrid Mixture-of-Experts (MoE) architecture combined with a Gated DeltaNet (a form of linear attention), which allows it to handle extremely long contexts more efficiently than standard Transformers.
- Total Parameters: 397 Billion
- Active Parameters: 17 Billion (per token)
- Layers: 60
- Hidden Dimension: 4,096
- Experts: 512 total experts (10 routed + 1 shared expert activated per token).
- Context Window: 262,144 tokens (native), extensible up to 1.01 million tokens via YaRN RoPE scaling.
- Tokenizer: 248,320 vocabulary size, supporting 201 languages.
2. Training Details
While Alibaba does not disclose the specific datasets, the training involved several advanced techniques:
- Data Scale: Trillions of multimodal tokens covering text, images, and video.
- Multi-Token Prediction (MTP): Trained with multi-step prediction to improve long-horizon reasoning and planning.
- Early Fusion: A unified multimodal backbone where vision and language tokens are processed in the same latent space from the start.
- Post-Training: Extensive Reinforcement Learning (RL) was used to enhance “Thinking Mode” (internal reasoning) and agentic capabilities.
3. Hardware & Estimated Costs
The model is optimized for NVIDIA GPU-accelerated systems (H100/H200/B200 clusters).
- Card Requirements: Due to its 397B total parameters, even with 4-bit quantization (~200GB+ VRAM), it typically requires a multi-GPU setup (e.g., 8x H100 80GB or 4x B200) just for inference. Training such a model would require thousands of interconnected GPUs.
- API Costs (per 1M tokens): * Input: ~$0.39 - $0.60
- Output: ~$2.34 - $3.60
- Estimated Compute Cost/Hour: To rent an 8x H100 node (capable of serving this model at high throughput), market rates in 2026 hover around $20 - $35 per hour depending on the provider (e.g., Together AI, Lambda, or Alibaba Cloud).
References:
- Qwen3.5-397B-A17B Model Card on NVIDIA NIM
- Qwen/Qwen3.5-397B-A17B on Hugging Face
- Artificial Analysis: Qwen3.5-397B-A17B Performance & Specs