Research

GAUGE · Embeddings

Embeddings.

Retrieve the right items by vector similarity.

embed.example_retrieval
recall@5 · n = 201 · margin ±6.7

Retrieve labelled routing examples for a question (recall, and whether the majority label matches the route).

020406080100recall@538.2
Top of the tied group
6 models, not separated
highest point estimate 38.2 ±6.7, at n = 201
020406080100tied range32.9+
Tied with the best
6 models
within 6.7 of the best
.0001.001.01.11$ / 1k queries · log$0.00053
Cheapest API among tied
text-embedding-3-small
$0.00053 per 1,000 queries
020406080100recall@538.2
Best local model
snowflake-arctic-embed2
38.2 ±6.7 · tied
ModelTypeScore ± 95%nLabel matchEmbed time$ / 1k queries
snowflake-arctic-embed2Local38.2 ±6.720126.3%4.8 s—
nomic-embed-text-v2-moeLocal37.3 ±6.620130.0%4 s—
text-embedding-3-largeAPI36.8 ±6.620127.5%4.4 s$0.0035
text-embedding-3-smallAPI34.7 ±6.520126.3%3 s$0.00053
qwen3-embedding:0.6bLocal34.6 ±6.520128.6%6.4 s—
qwen3-embedding:8bLocal32.9 ±6.520129.9%26.9 s—
granite-embedding:278mLocal30.3 ±6.320126.3%3.7 s—
bge-m3Local29.9 ±6.320130.0%4.6 s—
embeddinggemma-2:570mLocal29.4 ±6.320126.3%6.1 s—
embeddinggemma-2:740mLocal29.4 ±6.320126.3%5.7 s—
gemini-embedding-001API29.2 ±6.320127.5%6.8 s$0.0032
gemini-embedding-2API28.7 ±6.220126.3%7.7 s$0.0058
paraphrase-multilingualLocal26.9 ±6.120126.3%3.9 s—

Amber edge and bar: tied with the best (score ≥ best − its 95% margin, harness rule). Only rows with the task's full n are compared.

embed.task_retrieval
recall@5 · n = 100 · margin ±8.4

Retrieve the labelled example emails the classifier is shown for an incoming email (embedding recall against the platform's top 5).

020406080100recall@524.8
Top of the tied group
13 models, not separated
highest point estimate 24.8 ±8.4, at n = 100
020406080100tied range18.4+
Tied with the best
13 models
within 8.4 of the best
.0001.001.01.11$ / 1k queries · log$0.011
Cheapest API among tied
text-embedding-3-small
$0.011 per 1,000 queries
020406080100recall@524.2
Best local model
nomic-embed-text-v2-moe
24.2 ±8.3 · tied
ModelTypeScore ± 95%nLabel matchEmbed time$ / 1k queries
text-embedding-3-largeAPI24.8 ±8.4100—3.3 s$0.072
nomic-embed-text-v2-moeLocal24.2 ±8.3100—3.3 s—
bge-m3Local22.6 ±8.2100—5.2 s—
qwen3-embedding:8bLocal22.0 ±8.1100—66 s—
gemini-embedding-2API22.0 ±8.1100—4.8 s$0.084
text-embedding-3-smallAPI21.2 ±8.0100—3.1 s$0.011
embeddinggemma-2:570mLocal21.0 ±8.0100—5.9 s—
embeddinggemma-2:740mLocal21.0 ±8.0100—5.8 s—
qwen3-embedding:0.6bLocal20.4 ±7.9100—8.4 s—
paraphrase-multilingualLocal19.8 ±7.8100—2.6 s—
snowflake-arctic-embed2Local19.4 ±7.8100—5 s—
granite-embedding:278mLocal18.4 ±7.6100—2.9 s—
gemini-embedding-001API18.4 ±7.6100—4.5 s$0.062

Amber edge and bar: tied with the best (score ≥ best − its 95% margin, harness rule). Only rows with the task's full n are compared.