intfloat
Intfloat: E5-Large-v2
intfloat/e5-large-v2
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
intfloat/e5-large-v2 is a text-to-embeddings model from Intfloat. OpenRouter’s catalog describes it as producing 1024-dimensional dense vectors for English sentences, paragraphs, and documents, with a 512-token context. The accompanying Hugging Face model documentation reports MTEB evaluation entries spanning classification, retrieval, clustering, reranking, and semantic textual similarity, but the supplied evidence does not include license terms, deployment requirements, or independent workload testing. It is positioned for embedding-based search and similarity workflows rather than text generation.[1][2]
Strengths
- Catalog-reported output is a 1024-dimensional dense embedding designed for semantic retrieval and similarity tasks.[1]
- Model documentation reports evaluations across several MTEB task families, including retrieval, reranking, classification, clustering, and STS.[2]
- The catalog specifies text input and embeddings output, making the intended interface explicit.[1]
Limitations
- English is the only language explicitly described in the supplied catalog text; broader multilingual performance is not evidenced.[1]
- The catalog lists a 512-token context, so longer inputs may need chunking and validation.[1]
- The source pack does not document license terms, hardware needs, latency, supported API parameters, or safety behavior; real workloads should be validated.[1][2]
Where to use it
- Semantic search or retrieval over English documents that fit within the stated context.[1]
- A candidate for reranking or similarity-scoring pipelines built around embeddings.[1]
- Could be evaluated for clustering or classification with embeddings, using the documented MTEB coverage as a starting point rather than a guarantee.[2]
Sources
- [1] OpenRouter catalog · Intfloat: E5-Large-v2Sources checked: Nov 13, 2026
- [2] Model documentation · Intfloat: E5-Large-v2Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
The e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic search, reranking, and similarity-scoring tasks.
Specifications
- Model ID
- intfloat/e5-large-v2
- Canonical ID
- intfloat/e5-large-v2-20251117
- Creator
- intfloat
- Added to OpenRouter
- 18.11.2025
- Context length
- 512
- Modality
- text->embeddings
- Input modalities
- text
- Output modalities
- embeddings
- Token pricing
- USD per 1M tokens: in $0.010 / out $0
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | No measurement | — |
| Agents | No measurement | — |
| Writing | No measurement | — |
| Reasoning | No measurement | — |
| Document analysis | No measurement | — |
| Vision | No measurement | — |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | output: embeddings |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| DeepInfra | 512 | $0.010 | $0 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.