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by Ryan Lindsey · 2026-07-09

Dedicated GB10 hardware for Qwen 2.5 models significantly reduces the impact of noisy-neighbor latency, a common issue in multi-tenant environments. This post explores the benefits of hardware isolation and explains why p99 latency is crucial for maintaining service reliability.

The Problem with Multi-Tenant Environments

In multi-tenant environments, shared resources can lead to performance degradation due to noisy neighbors. This phenomenon occurs when one user's workload spikes, impacting the performance of other tenants on the same hardware. The average latency is often used to measure performance, but it doesn't account for the worst-case scenarios that can severely impact user experience.

Hardware Isolation with Dedicated GB10

Dedicated GB10 hardware offers a solution by providing each user with their own hardware resources. This isolation ensures that the performance of one user does not affect others, leading to more predictable and consistent performance.

Why p99 Latency Matters

p99 latency is the 99th percentile of latency, representing the worst-case scenario that 99% of requests do not exceed. This metric is critical for service reliability because it indicates the maximum delay that users might experience. In contrast, average latency can mask significant performance issues by averaging out the best and worst cases.

Quantifying the Advantage

Let's compare the performance of a multi-tenant environment with a dedicated GB10 setup. In a multi-tenant setup, the p99 latency might be 500ms, whereas with dedicated GB10, the p99 latency drops to 100ms. This reduction in p99 latency ensures that even in the worst-case scenarios, the service remains responsive and reliable.

Cost-Effective Performance

Our pricing model offers cost-effective performance with the added benefit of hardware isolation. For instance, the Business plan at $1999/mo provides 60.0M tokens at $33/1M, making it 60-80% cheaper than competitors like Anthropic or OpenAI.

Practical Implementation

To implement dedicated GB10 for Qwen 2.5, you can use our OpenAI-compatible API at /v1/chat with Bearer token authentication. Here's a sample code block to get you started:

import requests

headers = {
    'Authorization': 'Bearer YOUR_BEARER_TOKEN',
    'Content-Type': 'application/json'
}

response = requests.post('https://zcx.zctechnologies.org/v1/chat', headers=headers, json={
    'model': 'qwen2.5:72b',
    'messages': [{'role': 'user', 'content': 'What is the weather like today?'}]
})

print(response.json())

Conclusion

Dedicated GB10 hardware for Qwen 2.5 models provides a significant advantage in terms of reducing noisy-neighbor latency and ensuring consistent performance. To learn more about our plans and pricing, visit https://zcx.zctechnologies.org#plans and sign up for a prepaid LLM credit line.