Cohere launches Rerank 5 Pro and Fast: tops BRIGHT at 82.2 (+5.8 over Voyage Rerank 3), adds Context Focus passage pruning that cut agent tokens 35% while raising accuracy, and probability-calibrated relevance scores

Why it matters

【Key points】

Cohere released Rerank 5 on Oct 21 in Pro and Fast tiers, generally available on the Cohere API, Model Vault, Microsoft Foundry, Amazon SageMaker and North, plus VPC/on-prem. API price is $0.05 (Pro) and $0.02 (Fast) per 1M tokens.

1. Self-reported scores (RCP-nDCG@10): Pro ranks first on 39 of 46 composite datasets; 82.2 on reasoning-heavy BRIGHT, +5.8 over Voyage AI Rerank 3 and +12.4 over Rerank 4 Pro. Fast beats Voyage Rerank 3 Lite and the larger Qwen3-Reranker-8B on all four headline benchmarks.

2. Context Focus returns the most relevant passages inside each document in the same call. Cutting half the context kept ~96% answer quality; in a search-agent test the full stack used 35% fewer tokens than BM25 alone with accuracy up from 46% to 58%.

3. Calibrated scores read as probabilities (0.7 ≈ 70% useful); expected calibration error ~0.06 vs roughly 4x or more for rivals.

4. Fast handles ~187 1K-token docs/s on one A100, 2.9x Pro's throughput.

【Verifiable】

https://cohere.com/blog/rerank-5

https://x.com/cohere/status/2112923503100125326

【Our read】

1. Background: agents run dozens of searches per task, so retrieval quality and context length drive token bills; Cohere turns reranking into choosing which sentences reach the model.

2. Comparison: main rivals are Voyage AI (MongoDB) Rerank 3 and open Qwen3-Reranker. The differentiators are Context Focus (replacing a separate compression step) and calibrated thresholds that let agents tell when nothing relevant came back.

3. Impact: direct cost savings for enterprise search and support RAG, part of a wider shift, alongside OpenAI's longer prompt caching and Anthropic's cheaper cache reads, toward spending fewer tokens.

4. Caveats: Cohere's own RCP-nDCG metric isn't directly comparable to standard nDCG; the agent test used GLM-5.3 Flash; weights are closed.