Iluvatar BI-150/BI-V150
Vendor: Iluvatar
Category: GPU Graphics Processor
Architecture: Tianguai Architecture
Introduction
Iluvatar domestic GPU. BI-150 is a cloud training-inference card, BI-V150 is the next-gen product. Supports CUDA-compatible ecosystem, 2025 revenue 1.034 billion RMB, listed on Hong Kong Stock Exchange.
Specifications
| Model | Compute | Memory | Interface | TDP | Process |
|---|---|---|---|---|---|
| Tianguai 150 (BI-V150) | 256 TFLOPS (FP16) / 384 (INT8) | 64GB HBM2e (1.6 TB/s) | OAM | 350W | 7nm |
| Tianguai 100 (BI-V100) | 147 TFLOPS (FP16) / 295 (INT8) | 32GB HBM2 (1.2 TB/s) | PCIe 4.0 | 250W | 7nm |
| Zhikai 100 | 200 TOPS (INT8) | 32GB GDDR6 | PCIe 4.0 | 150W | 12nm |
Official Website
Driver Downloads
Linux
Related Documentation
OS Support
| Windows | Linux | macOS | Android |
|---|---|---|---|
| ❌ | ✅ | ❌ | ❌ |
Version History
| Version | Release Date | Description |
|---|---|---|
| BI-V 2.0 | 2023 | PyTorch compatibility layer |
Performance Benchmarks
| Model | Task | Performance Metric |
|---|---|---|
| Tianguai 100 | BF16 Training | Near A100 efficiency |
| Tianguai 100 | Inference Throughput | INT8 optimized inference |
| Zhikai 100 | Inference/Compute | Low-power inference scenarios |
Pricing
| Model | Reference Price | Notes |
|---|---|---|
| Tianguai 100 | Contact vendor | Enterprise AI accelerator |
| Zhikai 100 | Contact vendor | Inference-dedicated card |
Quick Installation
Linux
# 1. Install Iluvatar driver
sudo rpm -ivh iluvatar-driver-*.rpm
# 2. Install SDK
tar -xzf iluvatar-sdk-*.tar.gz && sudo ./install.sh
# 3. Verify
iluvatar-smi
Code Examples
Python (Iluvatar BI-ACC)
import torch
# Tianguai GPU supports CUDA-compatible mode
assert torch.cuda.is_available()
print(f"GPU: {torch.cuda.get_device_name(0)}")
Architecture Highlights
- Tianguai Architecture: Iluvatar proprietary GPGPU architecture, CUDA programming model compatible
- Zhikai Series: Compact accelerator card for low-power inference scenarios
- Domestic Ecosystem: Supports mainstream domestic OS (Kylin / UOS)
Model Compatibility
| Model/Framework | Support | Notes |
|---|---|---|
| PyTorch | ✅ Compatible | CUDA-compatible backend |
| PaddlePaddle | ⚠️ | Under adaptation |
| Large Model Inference | ⚠️ | Ecosystem developing |
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