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GTE-Qwen2-7B-Instruct

Alibaba's 7B instruction-tuned embedder that ranked #1 on MTEB in both English and Chinese

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About

GTE-Qwen2-7B-Instruct builds on the Qwen2-7B decoder with bidirectional attention grafted in, producing 3584-dimensional embeddings over a 32K-token window. Released June 16, 2024, it ranked first on both the English and Chinese MTEB evaluations — a rare bilingual double — and Alibaba reports an MTEB average of 70.24. It uses instruction prefixes for asymmetric retrieval (queries and documents get different prompts). The practical catches: it needs trust_remote_code and bfloat16 to load correctly (the MTEB team documented silent quality collapse on wrong configs), and like all 7B embedders it is GPU-hungry. Alibaba also sells a separate commercial embedding API, so the open weights and the paid service are not the same model.

Specs

Context window

32,768 tokens

Pricing

Free (open weights); Alibaba Cloud commercial embedding API billed separately

Free quota

None (self-hosted model)

API access

No official API for the open model; self-host via sentence-transformers (requires trust_remote_code)

Weights

Open weights

Released

June 16, 2024

Benchmarks

MTEB average 70.24; C-MTEB 72.05 (Alibaba-reported)

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

multilingual retrievallong-document RAGcross-lingual searchhigh-accuracy semantic search

Trust score — 8/10

/10 trustVerified

Scored 8/10 (verified tier, metrics-v1). Evidence: June 16, 2024 release date verified in xorbitsai integration issue; 3584 dims, 32K context, Apache 2.0 corroborated across MTEB loader docs and model directory pages.; MTEB 70.24 / C-MTEB 72.05 are Alibaba-reported figures — labeled as such in the entry.; MTEB team's documented loader pitfalls (bf16, trust_remote_code) add credibility to the technical details..

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Sources