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Open weightsInfiniflow (infly)/10 trustVerified

Inf-Retriever-v1

7B-class bilingual embedding that topped the AIR-Bench leaderboard in early 2025, fine-tuned from gte-Qwen2-7B-instruct.

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About

Inf-Retriever-v1 is the flagship embedding model from Infiniflow (publishing as infly on Hugging Face), released in late 2024 as a fine-tune of Alibaba's gte-Qwen2-7B-instruct. It targets Chinese and English retrieval with a 32K-token input window, making it one of the few long-context bilingual embedding models with fully open Apache 2.0 weights.

The model card reports an average score of 52.56 on the AIR-Bench heterogeneous retrieval leaderboard, which it topped as of January 2025, beating its own base model and BGE-Multilingual-Gemma2 across wiki, web, healthcare, law, and news splits. A smaller 1.5B variant (inf-retriever-v1-1.5b) has seen far wider adoption than the 8B flagship, which suggests the headline model is best for those who can afford the compute.

Specs

Context window

32,768 tokens

Pricing

Free / open weights (Apache 2.0)

Free quota

Free / open weights — self-host at no license cost

API access

Hugging Face weights (infly/inf-retriever-v1, infly/inf-retriever-v1-1.5b); self-hosted, no official API

Weights

Open weights

Released

Not disclosed

Benchmarks

  • AIR-Bench average: 52.56, leaderboard-top as of Jan 23, 2025 (author-reported, model card)
  • Beats gte-Qwen2-7B-instruct (48.38) and BGE-Multilingual-Gemma2 (46.83) on the same board (author-reported)
  • Full per-task model-index scores published in the model card

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

Use cases

bilingual-retrievallong-context-searchchinese-english-ragself-hosted-embeddings

Trust score — 6/10

/10 trustVerified

Scored 6/10 (verified tier, metrics-v1). Evidence: HF API confirms Apache 2.0 license and Dec 2024 release; AIR-Bench 52.56 figure taken from the authors' own model card table. Strengths: genuinely open license, strong author-reported multilingual scores, long context. Docked for: (1) only ~750 HF downloads on the 8B flagship, so real-world validation is thin; (2) no peer-reviewed paper, all figures author-reported; (3) the 1.5B variant is the one the community actually uses.

How the trust score is built

Full methodology →
Adoption · stars/downloads, log-scaled vs peers
4.0/10
Maintenance · recency, releases, issue load
6.0/10
Openness · license + docs
10.0/10
Manual review · sanity read + red-flag check
6.0/10
  • · HF API confirms Apache 2.0 and Dec 2024 release; 7B-class fine-tune of gte-Qwen2-7B-instruct, 32K context
  • · AIR-Bench 52.56 leaderboard-top (Jan 2025) is author-reported in the model card
  • · Only ~750 HF downloads on the 8B flagship; the 1.5B variant has ~24K downloads
  • · No peer-reviewed paper; all figures author-reported

Sources