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README.md

@@ -100,7 +100,7 @@ pipeline_tag: sentence-similarity
 
 > Small English text embedding model for semantic search, RAG, vector search, clustering, classification, and agent memory — MTEB 53.06, 3.5M parameters, 1024-token context
 
-**Ogma Mini** is built for edge and resource-constrained deployment. At 3.5M parameters and 14 MB it scores **53.06 MTEB** in our 54-task run while fitting in a fraction of the memory of 32M-parameter baselines. Ideal for mobile, IoT, browser, and serverless embedding workloads.
+**Ogma Mini** is built for edge and resource-constrained deployment. At 3.5M parameters and 14 MB it scores **53.06 MTEB** in our 66-task run while fitting in a fraction of the memory of 32M-parameter baselines. Ideal for mobile, IoT, browser, and serverless embedding workloads.
 
 ## Why the name Ogma?
 
@@ -136,9 +136,9 @@ Choose ogma-mini when you want a stronger model than micro while staying tiny en
 
 ## Performance
 
-### MTEB English — 54/54 tasks (category-averaged)
+### MTEB English — 66/66 tasks (category-averaged)
 
-Benchmarked with [MTEB](https://github.com/embeddings-benchmark/mteb) v2.10.7 on the standard 54-task English benchmark using category averaging (same methodology as the MTEB leaderboard).
+Benchmarked with [MTEB](https://github.com/embeddings-benchmark/mteb) v2.10.7 on the standard 66-task English benchmark using category averaging (same methodology as the MTEB leaderboard).
 
 | Category | ogma-mini | all-MiniLM-L6-v2 | Δ vs MiniLM |
 |---|---|---|---|
@@ -333,7 +333,7 @@ for d in model.config.matryoshka_dims:
 | *potion-base-32M* | 32.0M | 123 MB | *51.22* | 66.0 | 39.2 | 78.2 | 50.9 | 32.2 | 73.9 | 29.8 | 256 | inf |
 | *potion-base-8M* | 7.6M | 29 MB | *50.03* | 64.44 | 32.93 | 76.62 | 49.73 | 31.71 | 73.24 | 29.28 | 256 | inf |
 
-All Ogma: MTEB 2.10.7, 54-task standard English set, category-averaged.
+All Ogma: MTEB 2.10.7, 66-task standard English set, category-averaged.
 MiniLM/Potion: published scores from the [Model2Vec results page](https://github.com/MinishLab/model2vec/blob/main/results/README.md).
 
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