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+---
+title: "Approaching frontier performance for 1/30th the cost"
+description: "Using goose with MiniMax M2.5 on the Databricks OfficeQA benchmark"
+authors:
+ - mic
+---
+
+Quick highlight: [Sentient AGI](https://x.com/SentientAGI/status/2046967422004154739) recently shared with us some results with a challenge called "Grounded Reasoning" where teams tackled the Databricks OfficeQA benchmark using the MiniMax (2.5) open model.
+
+Highlights from the linked article:
+
+> * Using goose with [MiniMax M2.5](https://www.minimax.io/) on the [OfficeQA benchmark from Databricks](https://www.databricks.com/blog/officeqa), we're seeing results approaching frontier model performance for **1/30th of the cost**.
+> * Closed-source wins on accuracy (~80% vs ~70%), but MiniMax M2.5 ran at an average of $1.74 per run versus $56.53 for Opus 4.5. That's roughly 30× cheaper.
+> * Switching to the @goose_oss harness beat alternatives by ~10% in accuracy and was 8× cheaper than the next option. We decided to further investigate this with independent testing. On Terminal Bench 2.0, we found a similar story—goose was 20x more token efficient (and cheaper) than OpenHands, and more than 40x cheaper than OpenCode.
+
+Check out the full post and results here:
+
+> **[https://x.com/SentientAGI/status/2046967422004154739](https://x.com/SentientAGI/status/2046967422004154739)**
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