# How DigitalOcean optimized DeepSeek V3.2, MiniMax-M2.5, and Qwen 3.5 397B for Serverless Inference

DevFeed: [How DigitalOcean optimized DeepSeek V3.2, MiniMax-M2.5, and Qwen 3.5 397B for Serverless Inference](<https://devfeed.tech/articles/how-we-built-the-most-performant-deepseek-v3-2-minimax-m2-5-and-qwen-3-5-397b-on-digitalocean-serverless-inference-19888.md>)

Original publisher: [Read original article](<https://www.digitalocean.com/blog/how-we-built-fastest-deepseek-minimax-qwen-on-blackwell-ultra>)

Author: Bhaskar Dutt

Published: 2026-04-28T09:00:00Z

Content type: article

Language: en

Sources: [DigitalOcean](<https://devfeed.tech/sources/digitalocean.md>)

Topics: [Digital Ocean](<https://devfeed.tech/topics/digital-ocean.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [Low-Latency Inference](<https://devfeed.tech/topics/low-latency-inference.md>), [qwen](<https://devfeed.tech/topics/qwen.md>), [Serverless](<https://devfeed.tech/topics/serverless.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Optimization](<https://devfeed.tech/topics/optimization.md>)

Tags: [deepseek](<https://devfeed.tech/tags/deepseek.md>), [digitalocean](<https://devfeed.tech/tags/digitalocean.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [inference](<https://devfeed.tech/tags/inference.md>), [low-latency-inference](<https://devfeed.tech/tags/low-latency-inference.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [performance](<https://devfeed.tech/tags/performance.md>), [qwen](<https://devfeed.tech/tags/qwen.md>), [serverless](<https://devfeed.tech/tags/serverless.md>)

## AI overview

DigitalOcean announces general availability of DeepSeek V3.2, MiniMax-M2.5, and Qwen 3.5 397B on DigitalOcean Serverless Inference. The article describes GPU-level optimization and serving-stack tuning, reporting 230 output tokens per second and sub-one-second time to first token for DeepSeek V3.2, plus top output-speed results in Artificial Analysis testing for DeepSeek V3.2 and Qwen 3.5 397B.

## Source excerpt

Today at Deploy, we are announcing the general availability of DeepSeek V3.2, MiniMax-M2.5, and Qwen 3.5 397B on DigitalOcean Serverless Inference. On DeepSeek V3.2 and Qwen 3.5 397B, we deliver #1 output speed across all providers Artificial Analysis tested. On DeepSeek V3.2 specifically, that translates to 230 output tokens per second and sub-1-second Time-to-First-Token (TTFT) for 10,000 input tokens. This post covers how we got there: the GPU-level work, the serving stack tuning, and the specific technical tradeoffs we made along the way. Why fast inference matters The focus in AI development has fundamentally shifted from the training of models to the efficiency of inference. This shift is driven by the proliferation of agentic workloads, copilots, and real-time systems that form the core of next-generation AI applications. For these applications, speed is no longer just a performance metric; it is the critical differentiator between an engaging product and one that users abandon. Specifically, low-latency inference is essential for a seamless end-user experience. For highly interactive applications like conversational agents and voice interfaces, any delay beyond a sub-1-second TTFT is perceived as sluggish. The importance of fast inference is compounded by the complexity of modern AI workflows. An agentic task, for instance, often involves dozens of sequential model calls, where even minute Time-Per-Output-Token (TPOT) delays can accumulate into several seconds of user-visible latency. Quick inference also helps businesses by providing reliable performance and lower costs. Optimization in this area, such as that provided by DigitalOcean's inference engine, allows enterprises to achieve superior token economics, sustained throughput, and predictable latency, which are essential for scaling their AI-native applications reliably and affordably. Leading the Artificial Analysis benchmarks on speed The benchmarks we're publishing today reflect this. On DeepSeek V3.