Cambricon MLU270 (Siyuan 270)
Product Overview
The Cambricon MLU270 (Siyuan 270) is Cambricon's second-generation cloud AI chip, officially released in 2019, built on the MLUv02 architecture and positioned for high energy-efficiency AI inference acceleration in the cloud and at the edge. Compared with the first-generation MLU100, theoretical peak performance on non-sparse models improved 4× to 128 TOPS (INT8), while remaining compatible with INT4 (256 TOPS) and INT16 (64 TOPS), plus FP16/FP32 mixed precision.
The MLU270 is a key part of Cambricon's "cloud-edge-terminal" product lineup: cloud inference is delivered in accelerator card form factors such as the MLU270-S4 (70W) and MLU270-F4 (150W), with ample hardware video/image codec units for vision scenarios, suited to data center video analytics, smart cities, and other inference workloads. It forms a complete generational sequence with the subsequent MLU290 (training), MLU370 (Chiplet training-inference integrated), and MLU590 (third-generation flagship).
Core Specifications
| Parameter | Value |
|---|---|
| Architecture | Cambricon MLUv02 |
| Process Node | TSMC 16nm |
| INT8 Compute | 128 TOPS |
| INT4 Compute | 256 TOPS |
| INT16 Compute | 64 TOPS |
| FP16 / BF16 Compute | Not disclosed (mixed precision supported; peak not published) |
| FP32 Compute | Not disclosed |
| Memory Capacity | 16 GB |
| Memory Type | DDR4 (ECC) |
| Memory Bus Width | 256 bit |
| Memory Bandwidth | 102 GB/s |
| TDP | 70 W (MLU270-S4) / 150 W (MLU270-F4) |
| Interconnect | PCIe 3.0 ×16 |
| Interface | PCIe ×16 (S4 half-height half-length / F4 full-height full-length dual-slot) |
| Video Codec | Hardware codec units (video/image) |
| Launch | 2019 |
| Mass Production/Availability | In mass production |
⚠️ Specification notes: The memory type is DDR4 (ECC); some early sources loosely recorded it as "LPDDR/onboard memory". Follow the Cambricon official product pages (MLU270-S4/F4): 16GB DDR4 ECC / 102 GB/s. FP16/FP32 peak compute is not published on the official site; only mixed-precision support is confirmed.
Key Features
- MLUv02 architecture: based on a network-on-chip (NoC) that guarantees parallel efficiency across the chip's 16 tensor cores; hardware on-chip data compression improves effective cache capacity and bandwidth
- High energy-efficiency inference: INT8 inference performance improved 4× over the first generation, offering roughly 40× the energy efficiency of a CPU
- Rich precision support: INT4/INT8/INT16 + FP16/FP32 mixed precision
- Video/vision optimization: integrated ample hardware video/image codec units, suited to video analytics and smart cities
- Unified edge-cloud software: supports Cambricon NeuWare / MagicMind, compatible with mainstream frameworks such as TensorFlow, PyTorch, Caffe, and MXNet
Vendor Information
| Item | Details |
|---|---|
| Company | Cambricon Technologies Corporation Limited |
| Headquarters | Beijing |
| Founded | 2016 |
| IPO | STAR Market 688256 |
Use Cases
- ✅ Cloud AI inference (vision, speech, NLP, recommendation)
- ✅ Video analytics / smart cities (hardware codec units)
- ✅ Edge/non-data-center inference (F4 active cooling, deployable in workstations)
- ✅ Traditional machine learning acceleration
- ❌ Large-scale model training (positioned for inference; compute and memory constrained)
- ❌ Strong CUDA ecosystem dependence (requires migration to Cambricon NeuWare)
Related Cards
- Cambricon MLU590 (Siyuan 590) — Third-generation flagship training-inference card (generational successor)
- Cambricon MLU370 (Siyuan 370) — Chiplet training-inference integrated card
- Cambricon MLU290 (Siyuan 290) — Same-generation training card
- Cambricon MLU220 (Siyuan 220) — Edge/in-vehicle inference SoC
- Cambricon MLU690 — Next-generation flagship (planned)