Zencoder uses Nebius AI Studio for open-model inference behind its coding assistant. Developer advocate Leon Malisov describes hosted models for code completion and help selecting, testing and integrating them. Zencoder also uses other model providers. Nebius’s August 2025 customer case describes the arrangement.
The case study also describes multi-node training on Nebius AI infrastructure to optimize and fine-tune models for software engineering tasks. AI Studio supplies inference, while Nebius provides model-selection and optimization guidance, early model access and architectural consulting. A September 2025 Nebius post reports 30M+ accepted code-completion characters and 200 ms p50 latency for the AI Studio inference response. The same post separately describes consistent sub-100 ms inference latency and rapid, flexible scaling without infrastructure overhead. Nebius also reports improved product reliability, customer adoption and reduced operational complexity for Zencoder.
The case study also describes continued use of AI Studio’s expanding model portfolio to develop next-generation autonomous coding agents. Planned tasks include technical-debt management, proactive bug detection and end-to-end testing automation.
Nebius states that Zencoder uses AI Studio for coding-assistant inference, flexible scaling, expert support and early model access. It describes consistent sub-100 ms inference latency and separately reports 30M+ accepted code-completion characters and 200 ms p50 latency for the AI Studio inference response. Nebius also reports improved product reliability, customer adoption and reduced operational complexity for Zencoder.
Nebius Zencoder inference customer announcement1 Sept 2025 · Nebius · Web pageNebius states that Zencoder uses AI Studio for coding-assistant inference, flexible scaling, expert support and early model access. It describes consistent sub-100 ms inference latency and separately reports 30M+ accepted code-completion characters and 200 ms p50 latency for the AI Studio inference response. Nebius also reports improved product reliability, customer adoption and reduced operational complexity for Zencoder.
Nebius Zencoder AI Studio customer case
18 Aug 2025 · Nebius · Web page
Describes Nebius-hosted model inference for Zencoder’s coding assistant.
Nebius Zencoder developer interview29 Aug 2025 · Nebius · Video · Starts at 0:40At 0:40, 2:58 and 4:14, Leon Malisov describes Nebius-hosted models, code completion and provider selection.
Zencoder develops AI agents for software developers, engineering teams and business users. Its Zenflow Code application coordinates agents to plan features, fix bugs, refactor code and verify changes against specifications. IDE Agents work inside VS Code and JetBrains editors to edit files, run tests and explore repositories. The platform indexes codebases to understand architecture and dependencies. Zenflow Work extends its agents to business workflows, connecting tools such as Jira, Slack and Notion to prepare release notes, meeting briefs and other deliverables.
AI coding agents and code completion · Developer tools
How they use Nebius
Zencoder uses Nebius AI Studio for open-model inference behind its coding assistant. Developer advocate Leon Malisov describes hosted models for code completion and help selecting, testing and integrating them. Zencoder also uses other model providers. Nebius’s August 2025 customer case describes the arrangement.
The case study also describes multi-node training on Nebius AI infrastructure to optimize and fine-tune models for software engineering tasks. AI Studio supplies inference, while Nebius provides model-selection and optimization guidance, early model access and architectural consulting. A September 2025 Nebius post reports 30M+ accepted code-completion characters and 200 ms p50 latency for the AI Studio inference response. The same post separately describes consistent sub-100 ms inference latency and rapid, flexible scaling without infrastructure overhead. Nebius also reports improved product reliability, customer adoption and reduced operational complexity for Zencoder.
The case study also describes continued use of AI Studio’s expanding model portfolio to develop next-generation autonomous coding agents. Planned tasks include technical-debt management, proactive bug detection and end-to-end testing automation.
Nebius states that Zencoder uses AI Studio for coding-assistant inference, flexible scaling, expert support and early model access. It describes consistent sub-100 ms inference latency and separately reports 30M+ accepted code-completion characters and 200 ms p50 latency for the AI Studio inference response. Nebius also reports improved product reliability, customer adoption and reduced operational complexity for Zencoder.
Nebius Zencoder inference customer announcement1 Sept 2025 · Nebius · Web pageNebius states that Zencoder uses AI Studio for coding-assistant inference, flexible scaling, expert support and early model access. It describes consistent sub-100 ms inference latency and separately reports 30M+ accepted code-completion characters and 200 ms p50 latency for the AI Studio inference response. Nebius also reports improved product reliability, customer adoption and reduced operational complexity for Zencoder.
Nebius Zencoder AI Studio customer case
18 Aug 2025 · Nebius · Web page
Describes Nebius-hosted model inference for Zencoder’s coding assistant.
Nebius Zencoder developer interview29 Aug 2025 · Nebius · Video · Starts at 0:40At 0:40, 2:58 and 4:14, Leon Malisov describes Nebius-hosted models, code completion and provider selection.
Zencoder develops AI agents for software developers, engineering teams and business users. Its Zenflow Code application coordinates agents to plan features, fix bugs, refactor code and verify changes against specifications. IDE Agents work inside VS Code and JetBrains editors to edit files, run tests and explore repositories. The platform indexes codebases to understand architecture and dependencies. Zenflow Work extends its agents to business workflows, connecting tools such as Jira, Slack and Notion to prepare release notes, meeting briefs and other deliverables.
