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Best local embedding model for job-posting search on a 16 GB M4 Mac?

A developer's benchmark of three local embedding models on a 16 GB M4 Mac found Qwen3-Embedding-4B (Q4 GGUF) reached 91% natural and 71% paraphrased top-5 retrieval accuracy on 56 job-posting questions against a 400-posting pool, versus 77% and 32% for bge-small-en-v1.5 and 79% and 45% for bge-large-en-v1.5. The trade-off is speed: Qwen3-Embedding-4B ran at 3.3 chunks/s (roughly 12 hours for the corpus), bge-small at 366 chunks/s (about 6 minutes), and bge-large at 34 chunks/s, with Qwen3-Embedding-0.6B now testing at about 19 chunks/s. Gopi Krishna Reddy Katkuri is seeking an English-only, locally runnable embedding model under about 3 GB of memory that is free to use.

read1 min views1 publishedOct 6, 2026

Hi all,

I’m building a local job-search assistant and I’m looking for the best

embedding model for it. Everything runs on my own machine, so speed and

memory matter as much as quality.

The setup

What I measured (56 postings, two questions each, pool of 400 postings;

“top 5” = the posting the question was written from is in the top 5)

| Model | Natural top 5 | Paraphrased top 5 | Speed |

|---|---|---|---|
| bge-small-en-v1.5 (current) | 77% | 32% | 366 chunks/s | 
| bge-large-en-v1.5 | 79% | 45% | 34 chunks/s | 
| Qwen3-Embedding-4B (Q4 GGUF) | 91% | 71% | 3.3 chunks/s | 

Qwen3-Embedding-4B is clearly the best, but it would take about 12 hours

to embed my corpus, against about 6 minutes for bge-small. I’m testing

Qwen3-Embedding-0.6B now (about 19 chunks/s so far). What I’m looking for

Constraints: English only, runs locally in under about 3 GB of memory,

free to use.

Thanks for any suggestions!

Gopi Krishna Reddy Katkuri

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