Agentic & Tool Use benchmark # GBAEval leaderboard > GBAEval results for 23 AI models, led by Claude Opus 5 at 79.6%. What the benchmark measures, who runs it, and a source for every score. - Canonical page: https://noometry.com/benchmarks/gbaeval - Last updated: 2026-10-10 - Title: GBAEval Leaderboard (October 2026): Scores by Model As of October 2026, Claude Opus 5 has the highest published GBAEval score on Noometry at 79.6%, out of 23 models with results. Last verified October 10, 2026 ## About GBAEval A description with primary sources is being prepared for this benchmark. - **Category:** [Agentic & Tool Use](https://noometry.com/best/agentic) - **Introduced:** 2026 - **Unit:** Percent (random guessing ≈ 0%) - **Official site:** [epoch.ai](https://epoch.ai/benchmarks) ## Top 15 models Top models on GBAEval 1. Claude Opus 5 79.6% 2. Claude Fable 5 74.5% 3. Claude Opus 4.8 70.9% 4. Grok 4.5 65.4% 5. Claude Sonnet 5 65.3% 6. GPT-5.5 53.2% 7. GPT-5.6 Sol 52.6% 8. Claude Sonnet 4.6 48.8% 9. Kimi K3 48.3% 10. GPT-5.4 45.1% 11. Claude Opus 4.6 44.1% 12. Claude Opus 4.7 43.8% 13. Muse Spark 1.1 7.9% 14. Gemini 3.5 Flash 6.7% 15. Grok Build 0.1 2.4% 16. 020406080 Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise) ## All results GBAEval results by model | # | Model | Provider | Score | Setting | Source | Date | | --- | --- | --- | --- | --- | --- | --- | | 1 | [Claude Opus 5](https://noometry.com/models/claude-opus-5) | [Anthropic](https://noometry.com/providers/anthropic) | 79.6% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 2 | [Claude Fable 5](https://noometry.com/models/claude-fable-5) | [Anthropic](https://noometry.com/providers/anthropic) | 74.5% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 3 | [Claude Opus 4.8](https://noometry.com/models/claude-opus-4-8) | [Anthropic](https://noometry.com/providers/anthropic) | 70.9% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 4 | [Grok 4.5](https://noometry.com/models/grok-4-5) | [xAI](https://noometry.com/providers/xai) | 65.4% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 5 | [Claude Sonnet 5](https://noometry.com/models/claude-sonnet-5) | [Anthropic](https://noometry.com/providers/anthropic) | 65.3% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 6 | [GPT-5.5](https://noometry.com/models/gpt-5-5) | [OpenAI](https://noometry.com/providers/openai) | 53.2% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 7 | [GPT-5.6 Sol](https://noometry.com/models/gpt-5-6-sol) | [OpenAI](https://noometry.com/providers/openai) | 52.6% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 8 | [Claude Sonnet 4.6](https://noometry.com/models/claude-sonnet-4-6) | [Anthropic](https://noometry.com/providers/anthropic) | 48.8% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 9 | [Kimi K3](https://noometry.com/models/kimi-k3) | [Moonshot AI](https://noometry.com/providers/moonshot) | 48.3% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 10 | [GPT-5.4](https://noometry.com/models/gpt-5-4) | [OpenAI](https://noometry.com/providers/openai) | 45.1% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 11 | [Claude Opus 4.6](https://noometry.com/models/claude-opus-4-6) | [Anthropic](https://noometry.com/providers/anthropic) | 44.1% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 12 | [Claude Opus 4.7](https://noometry.com/models/claude-opus-4-7) | [Anthropic](https://noometry.com/providers/anthropic) | 43.8% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 13 | [Muse Spark 1.1](https://noometry.com/models/muse-spark-1-1) | [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta) | 7.9% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 14 | [Gemini 3.5 Flash](https://noometry.com/models/gemini-3-5-flash) | [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 6.7% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 15 | [Grok Build 0.1](https://noometry.com/models/grok-build-0-1) | [xAI](https://noometry.com/providers/xai) | 2.4% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 16 | [MiniMax-M3](https://noometry.com/models/minimax-m3) | [![](/logos/minimax.svg) MiniMax](https://noometry.com/providers/minimax) | 0.9% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 17 | [Kimi K2.6](https://noometry.com/models/kimi-k2-6) | [Moonshot AI](https://noometry.com/providers/moonshot) | 0.9% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 18 | [Kimi K2.7 Code](https://noometry.com/models/kimi-k2-7-code) | [Moonshot AI](https://noometry.com/providers/moonshot) | 0.9% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 19 | [Gemini 3.1 Pro Preview](https://noometry.com/models/gemini-3-1-pro-preview) | [![](/logos/google.svg) Google](https://noometry.com/providers/google) | 0.8% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 20 | [Qwen3.7 Max](https://noometry.com/models/qwen3-7-max) | [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba) | 0.4% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 21 | [GLM-5.2](https://noometry.com/models/glm-5-2) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | 0% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 22 | [GLM-5.1](https://noometry.com/models/glm-5-1) | [Z.ai (Zhipu)](https://noometry.com/providers/zai) | 0% | | [Epoch AI](https://epoch.ai/benchmarks) | | | 23 | [MiniMax-M2.7](https://noometry.com/models/minimax-m2-7) | [![](/logos/minimax.svg) MiniMax](https://noometry.com/providers/minimax) | 0% | | [Epoch AI](https://epoch.ai/benchmarks) | | ## Compare the leaders - [Claude Opus 5 vs Claude Fable 5](https://noometry.com/compare/claude-fable-5-vs-claude-opus-5) - [Claude Opus 5 vs Claude Opus 4.8](https://noometry.com/compare/claude-opus-4-8-vs-claude-opus-5) - [Claude Opus 5 vs Grok 4.5](https://noometry.com/compare/claude-opus-5-vs-grok-4-5) - [Claude Opus 5 vs Claude Sonnet 5](https://noometry.com/compare/claude-opus-5-vs-claude-sonnet-5) - [Claude Fable 5 vs Claude Opus 4.8](https://noometry.com/compare/claude-fable-5-vs-claude-opus-4-8) - [Claude Fable 5 vs Grok 4.5](https://noometry.com/compare/claude-fable-5-vs-grok-4-5) ## Other agentic & tool use benchmarks - [Terminal-Bench](https://noometry.com/benchmarks/terminal-bench) - [APEX-Agents](https://noometry.com/benchmarks/apex-agents) - [Berkeley Function Calling Leaderboard](https://noometry.com/benchmarks/bfcl) - [OSWorld 2.0](https://noometry.com/benchmarks/osworld-2) - [GDPval](https://noometry.com/benchmarks/gdpval) - [Remote Labor Index](https://noometry.com/benchmarks/remote-labor-index) - [TheAgentCompany](https://noometry.com/benchmarks/the-agent-company) - [τ²-bench Airline](https://noometry.com/benchmarks/tau2-airline) - [τ²-bench Banking](https://noometry.com/benchmarks/tau2-banking) - [τ²-bench Retail](https://noometry.com/benchmarks/tau2-retail) - [τ²-bench Telecom](https://noometry.com/benchmarks/tau2-telecom) - [Cybench](https://noometry.com/benchmarks/cybench) ## Frequently asked questions ### Which model has the highest GBAEval score? As of October 2026, Claude Opus 5 has the highest published GBAEval score on Noometry at 79.6%, out of 23 models with results. ### What is the best open-weight model on GBAEval? Kimi K3 has the highest GBAEval accuracy among open-weight models at 48.3%, ranking 9 of 23 overall. ### Cite this page Noometry. (2026). GBAEval leaderboard. Retrieved October 10, 2026, from https://noometry.com/benchmarks/gbaeval Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/benchmarks/gbaeval.md).