Guanxingyun

Guanxingyun GPU pricing overview

Guanxingyun is a specialist GPU cloud provider headquartered in China. Guanxingyun is a Chinese GPU cloud provider offering Huawei 910B, A100 40GB, V100 32GB, and RTX 4090 GPU instances with CNY monthly pricing. The platform is notable for offering Huawei Ascend 910B hardware alongside NVIDIA GPUs, making it relevant for teams exploring domestic Chinese AI accelerators. Prices are denominated in CNY; USD equivalents are approximate. Verified 2026-10-22: Huawei 910B at CNY 3.26/hr, A100 40GB at CNY 3.58/hr, V100 32GB at CNY 1.72/hr. Billing is On-demand, Monthly with a minimum commitment of None. Available regions include CN. GPU instances can be provisioned on-demand, making Guanxingyun suitable for both short-duration experiments and sustained production workloads.

Guanxingyun vs other GPU providers

Guanxingyun competes with providers including Lambda Labs, CoreWeave, RunPod, Paperspace, Vast.ai, and the major hyperscalers (AWS, Google Cloud, Azure) for GPU compute workloads spanning LLM training, fine-tuning, and inference serving. Key differentiators include: Huawei Ascend 910B availability alongside NVIDIA GPUs; A100 and V100 at competitive CNY rates; China-based infrastructure for local data residency. Use the side-by-side comparison tool above to see Guanxingyun pricing against any other provider across shared GPU models. For a broader market view, the live GPU prices table shows all 4 Guanxingyun listings alongside 91+ providers in a single sortable view.

Best use cases for Guanxingyun

Guanxingyun is best suited for: Chinese AI teams exploring Huawei Ascend hardware, Teams requiring China data residency, Cost-sensitive GPU workloads within Chinese infrastructure. Support tiers range from Standard, making it viable for both individual researchers and enterprise teams with SLA requirements. There are currently 4 active GPU listings on Guanxingyun, covering Huawei 910B, A100 40GB, V100 32GB, RTX 4090. H100 SXM5 instances with NVLink interconnect are commonly used for large-scale training workloads. A100 40GB and RTX 4090 instances are frequently used for fine-tuning and inference of smaller models.

Guanxingyun billing model and cost structure

Guanxingyun uses On-demand, Monthly pricing. Spot pricing is not currently available on this provider — all instances are on-demand. Reserved instance pricing may be available for predictable long-running workloads — check the provider's pricing page for current committed-use rates. Always compare the effective hourly rate including egress, storage, and networking costs when evaluating total cost of ownership across providers.

Choosing the right GPU on Guanxingyun

GPU selection depends on model size, precision, and whether your workload is compute-bound or memory-bandwidth-bound. For LLM training above 30B parameters, H100 80GB SXM5 instances with NVLink are the standard choice — high HBM3 bandwidth and FP16 throughput make them well-suited for large transformer workloads. For inference of 7B–13B models in FP16 or BF16, A100 40GB is a common choice on many providers. RTX 4090 instances are widely used for fine-tuning, prototyping, and quantized inference (INT4/INT8) of models up to 70B. Read the H100 vs A100 guide or the GPU benchmarks for ML guide for a full breakdown.

How Guanxingyun pricing data is collected

Prices shown are sourced from Guanxingyun's public pricing API or pricing page and refreshed every 15 minutes. On-demand rates reflect the current list price for a single GPU instance in the cheapest available region. Spot prices, where available, reflect interruptible instance rates at the time of the last snapshot. All prices are in CNY per hour. Daily snapshots are kept in our history archive and visualised in the GPU price history charts — useful for identifying seasonal pricing patterns and evaluating whether current rates are above or below the 30-day average.

Evaluating managed LLM inference APIs as an alternative to self-hosted GPU compute? Compare live LLM token prices across OpenAI, Anthropic, Google, Groq, and many other providers. The cheapest GPU cloud guide covers the break-even analysis between self-hosted and managed inference at different request volumes.