cohere
Cohere: Rerank v3.5
cohere/rerank-v3.5
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to the OpenRouter catalog, Cohere: Rerank v3.5 is a text-to-rerank model intended to reorder search results for better relevance. The catalog reports support for multi-aspect and semi-structured data reranking across more than 100 languages, positioning it for refining semantic or keyword search output. It lists a 4,096-token context window and no benchmark data. This evidence pack contains only catalog information; an independent model card was not available, so real-world performance remains unverified.[1]
Strengths
Limitations
- Only OpenRouter catalog evidence was supplied; an independent model card was not available in this source pack.[1]
- No benchmark or measured performance data is listed, so quality claims are unverified and should be validated on your own workload.[1]
- The catalog lists no supported parameters, so tuning options are undocumented here.[1]
Where to use it
- Potentially useful as a second-stage reranker over semantic or keyword search results, per the catalog description.[1]
- Multilingual retrieval pipelines that need cross-language result ordering, subject to workload testing.[1]
- Reordering semi-structured records where multi-aspect ranking is needed, if it performs well in your evaluation.[1]
Sources
- [1] OpenRouter catalog · Cohere: Rerank v3.5Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Rerank v3.5 is designed to reorder search results for improved relevance. It supports multi-aspect and semi-structured data reranking over 100+ languages. Ideal for refining results from semantic or keyword search...
Specifications
- Model ID
- cohere/rerank-v3.5
- Creator
- cohere
- Added to OpenRouter
- 05.04.2026
- Context length
- 4,096
- Modality
- text->rerank
- Input modalities
- text
- Output modalities
- rerank
- Token pricing
- No per-token price in the source snapshot — see OpenRouter for the billing unit
- 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 | — |
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) |
|---|---|---|---|---|---|---|
| Amazon Bedrock | 4,096 | — | — | — | — | 100% |
| Amazon Bedrock | 4,096 | — | — | — | — | 100% |
| Cohere | 4,096 | — | — | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.