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GitLab

Rate limits on GitLab.com are changing Optimize your team See who spent your AI credits and set fair caps per team New MCP tools help platform teams scale automation safely GitLab Duo CLI takes a task from goal to done When to use SAST versus an LLM security scanner GitLab Dedicated: Compliance for a new regulatory era How to calculate DevOps platform total cost of ownership GitLab Critical Patch Release: 19.3.2, 19.2.6, 19.1.8 Co-Create: Building GitLab with our users Prepare for the Cyber Resilience Act Bring your own model to GitLab Duo Self-Hosted with Microsoft Foundry GitLab’s internal playbook to foster AI-fluent technical teams Critical remote code execution in vm2, a widely used Node.js sandbox library GitLab compliance frameworks: Adhere to SOC 2 in minutes How to recognize your team with GitLab Achievements Making room for what GitLab Patch Release: 19.3.1, 19.2.5, 19.1.7 Git was built for humans — agents need an upgrade Scale software delivery without owning the runner fleet When code is abundant When your backlog outgrows your team, GitLab scales remediation Run agentic software delivery inside the boundaries you already trust Build custom flows in minutes with the Flow Creator agent GitLab 19.3 release notes From chaos to context: Building an AI dev workflow From OpenTofu to Argo CD: GitLab as your AWS control plane Avoid the massive end-to-end tax of default full history clones GitLab Critical Patch Release: 19.2.4, 19.1.6, 19.0.8, 18.11.11 Critical remote code execution in Serena, a popular MCP coding agent
GPT-6 Astra on GitLab: Faster runs, fewer tokens used
Brittany Lutz · 2026-09-08 · via GitLab

OpenAI's newest frontier model GPT-6 Astra is now on GitLab Duo Agent Platform, delivering faster runs and lower token usage.

In GitLab's internal evaluation, GPT-6 Astra finished a typical run 43.4% faster than GPT-5.6 Sol and used 42.7% fewer tokens per run, while completing every task in the benchmark. For your team, that means agentic tasks such as dependency updates, build fixes, and small multi-file changes come back faster, and stretch your token budget across more of your team’s backlog.

Faster agentic work, even on your slowest runs

Wait time factors into how your team uses an agent. A run that comes back in a few minutes is one you stay engaged with. A longer run is one you let work in the background while you move to another task. When it finishes, you switch context from the work you're in, reread what you asked the agent for, and review a diff you last thought about 30 minutes ago.

The longer runs that result in context switching are the ones GPT-6 Astra shortened most in GitLab's internal testing. At the 95th percentile, the slower tail of its runs, GPT-6 Astra finished 49.2% faster than GPT-5.6 Sol, and 43.4% faster on a typical run.

Astra's slowest runs finish in roughly the time Sol needed for an average one. With GPT-6 Astra, your team waits less on high volume, routine work.

Every task finished, at a lower token usage per run

In GitLab's internal testing, GPT-6 Astra completed 100% of benchmark tasks. No run stalled, timed out, or came back empty, so your team isn't left waiting on runs that finish with nothing to review. Astra resolved 63.3% of those tasks, returning a change that passed the benchmark's tests, compared to a 76.7% resolution rate for GPT-5.6 Sol. Misses return as patches to correct rather than runs that produced nothing.

Astra reached its completion rate using 42.7% fewer tokens per run than Sol, measured across the same set of tasks. That savings compounds across a backlog, so your token budget covers more of the work your team delegates.

Where Astra saves your team the most

Many factors go into the model your team chooses to use for a particular task. GPT-6 Astra is a strong choice where turnaround and token consumption per run matter most, such as dependency updates, build fixes, and small multi-file changes. It fits the work your team reviews before it merges, while your team might prefer to use GPT-5.6 Sol when a change has to be right the first time.

With GitLab Duo Agent Platform, your admin sets the model per feature in model selection, so each workload your team sends to an agent runs on the model you chose for it. That flexibility comes with consistent governance, with every model going through the same context layer, policy checks, and audit trail.

Put Astra to work

GPT-6 Astra is available now on GitLab Duo Agent Platform and, like other models, runs on GitLab Credits. New to Duo Agent Platform? Start a free trial today. Already a GitLab Premium or Ultimate subscriber? Turn on Duo Agent Platform and use the GitLab Credits included with your subscription.