Which models does GitHub Copilot's harness support?

The harness supports 20+ frontier models across the GPT, Claude, Gemini, and MAI families, plus bring your own key for open-source and local models.

How does GitHub Copilot's performance compare to Claude Code and Codex CLI?

Task resolution rates are on par with model-vendor harnesses when using the same model and benchmark task, while showing lower token consumption across most configurations. On TerminalBench, GitHub Copilot's markers sit within overlapping variance ellipses with same-model competitors on both task completion and cost per task.

What unique capability does GitHub Copilot's multi-model architecture enable?

The multi-model design unlocks harness-level capabilities a model-vendor harness cannot offer—for example, Rubber Duck uses cross-model-family critique, where one model reviews another's work to improve outcomes beyond what any single model produces alone.

Large Language ModelsAI Coding AssistantsGitHub Copilot BlogJun 26, 2026Jun 26, 2026, 10:00 JST

GitHub Copilot matches rivals on fewer tokens

Send on LINE

3 Key Points

What happened
GitHub published benchmark results showing its Copilot agentic harness—the shared engine powering Copilot CLI, the Copilot app, and code review—achieves task-completion rates on par with Claude Code and Codex CLI across SWE-bench Verified, SWE-bench Pro, SkillsBench, and TerminalBench, while consuming fewer tokens in most configurations.
Why it matters
The harness supports 20+ frontier models across GPT, Claude, Gemini, and MAI families, plus open-source and local models, letting developers pick the right model for each task's cost and capability needs without being locked into a single vendor's tool. Lower token use translates to reduced API costs for equivalent work.
What to watch
GitHub's multi-model architecture enables cross-model critique (e.g., Rubber Duck, where one model reviews another's output), a capability single-model vendor harnesses cannot offer. The benchmarks show GPT models deliver the best value with strong resolution at lowest cost, while Claude Opus reaches the highest resolution at higher cost.

Not sure about something? Ask the AI

Questions and answers are published on this page.

Summaries like this, in your inbox every morning.

Get news like this every morning, free

FAQ

Which models does GitHub Copilot's harness support?: The harness supports 20+ frontier models across the GPT, Claude, Gemini, and MAI families, plus bring your own key for open-source and local models.
How does GitHub Copilot's performance compare to Claude Code and Codex CLI?: Task resolution rates are on par with model-vendor harnesses when using the same model and benchmark task, while showing lower token consumption across most configurations. On TerminalBench, GitHub Copilot's markers sit within overlapping variance ellipses with same-model competitors on both task completion and cost per task.
What unique capability does GitHub Copilot's multi-model architecture enable?: The multi-model design unlocks harness-level capabilities a model-vendor harness cannot offer—for example, Rubber Duck uses cross-model-family critique, where one model reviews another's work to improve outcomes beyond what any single model produces alone.

GitHub Copilot BlogRead Original Article

Send on LINE

AI news that matters for your work, delivered every morning.

Pick your industry and the AI tools you use, and get news related to your work every day.

Get it free

Free · 30 seconds with Google · unsubscribe anytimeWhat is AIToday? →

Ask AI

Ask AI anything about this article. The AI reads this article, earlier AIToday articles, and Wikipedia, and cites its sources. Q&As are published on this page for other readers too.