Best reranking model API
4 models · updated 2026-07-15
The verdict
Cohere Rerank leads — All 4 models rank Cohere Rerank the top pick.
As of 2026-07-15, ChatGPT, Claude, Gemini and Grok collectively rank Cohere Rerank #1 for reranking model api on ModelsAgree — a unanimous pick. The models' case: Best all-round production choice: excellent relevance quality, multilingual and structured-data support, 32K context, automatic long-document chunking, mature. The models' main caveat: Closed commercial model; Pro can be slower and costlier than leaner alternatives, so it is not ideal for strict data-sovereignty or self-hosting. The strongest alternative is Voyage Rerank — Near-tied with Cohere on general quality, with instruction-following, multilingual retrieval, 32K context, and especially strong value for. Source: https://modelsagree.com/best/best-reranking-model-api (modelsagree.com, CC BY 4.0).
Combined ranking
- 1GPT #1Claude #1Gemini #1Grok #1
Best all-round production choice: excellent relevance quality, multilingual and structured-data support, 32K context, automatic long-document chunking, mature integrations, and a faster sibling for latency-sensitive workloads
+ model takes & fixes− hide details
GPT Best all-round production choice: excellent relevance quality, multilingual and structured-data support, 32K context, automatic long-document chunking, mature integrations, and a faster sibling for latency-sensitive workloads
Claude Still the default commercial reranker for production RAG — consistently strong cross-domain and multilingual (100+ languages) relevance, dead-simple drop-in API, and the widest enterprise availability (native on AWS Bedrock, Azure AI, SageMaker, plus vector-DB integrations like Pinecone and Weaviate); assumes the typical practitioner values reliability and ecosystem reach over squeezing the last benchmark point
Gemini Provides the industry gold standard for out-of-the-box accuracy, natively supports semi-structured JSON input for complex database fields, and has a dedicated low-latency fast tier. Its top rank assumes the practitioner values zero-ops setup and maximum ecosystem integration over cost control.
Grok Best-in-class nDCG on BEIR + enterprise benchmarks (finance, healthcare, manufacturing) after late-2025 release; outperforms Voyage and Jina in head-to-heads; 100+ languages; simplest, most reliable API for RAG/agent pipelines with proven token reduction and accuracy lift.
Where it falls shortper GPT Closed commercial model; Pro can be slower and costlier than leaner alternatives, so it is not ideal for strict data-sovereignty or self-hosting requirements
per Claude Closed weights and per-1k-search pricing that gets expensive at high query volume; not for teams needing self-hosting or very long single-document scoring
per Gemini High pay-per-token API costs at scale and is entirely closed-source, making it unsuitable for local data sovereignty.
per Grok Add self-host or on-prem deployment options for data-sovereignty and regulated industries.
- 2GPT #2Claude #2Gemini #2Grok #2
Near-tied with Cohere on general quality, with instruction-following, multilingual retrieval, 32K context, and especially strong value for sophisticated RAG queries where ranking criteria need to be expressed in the query
+ model takes & fixes− hide details
GPT Near-tied with Cohere on general quality, with instruction-following, multilingual retrieval, 32K context, and especially strong value for sophisticated RAG queries where ranking criteria need to be expressed in the query
Claude Near-tie with Cohere on quality and often beats it on retrieval benchmarks, with much longer context per document, instruction-following reranking, and lower per-token pricing; MongoDB acquisition removed the startup-longevity risk
Gemini Offers class-leading instruction-following that lets developers dynamically steer relevance scoring (e.g., focusing on specific metadata). It is in a near-tie with Jina AI for the second spot, earning it due to superior instruction-adherence precision for agentic RAG, assuming an English-centric pipeline.
Grok Highest relevance lift in many independent RAG tests; longest context (16k tokens); excels on complex/domain-heavy retrieval (finance, legal).
Where it falls shortper GPT Smaller deployment and integration ecosystem than Cohere, making it less convenient for enterprises standardizing through multiple clouds and established search platforms
per Claude Thinner ecosystem — fewer cloud-marketplace and framework integrations than Cohere, and tighter rate limits on new accounts make it less turnkey for enterprise procurement
per Gemini Lacks robust multilingual support and has fewer native vector database integrations.
per Grok Cut p99 latency and per-query costs to win high-volume real-time workloads.
- 3GPT #3Claude #4Gemini #3Grok #3
Exceptional long-context and multilingual option with a 131K listwise architecture, open weights for non-commercial use, and an accessible hosted API; particularly strong for long documents and ranking candidates jointly rather than independently
+ model takes & fixes− hide details
GPT Exceptional long-context and multilingual option with a 131K listwise architecture, open weights for non-commercial use, and an accessible hosted API; particularly strong for long documents and ranking candidates jointly rather than independently
Gemini Combines a massive 131k token context window with the ability to process up to 64 documents concurrently, using a causal self-attention architecture. It is in a near-tie with Voyage AI, placed third due to slightly lower reasoning performance on complex domain-specific tasks.
Grok Lowest latency and highest throughput at scale; best long-context + multimodal (PDF/image) support; flexible API with open weights for customization or self-host hybrids.
Claude Best budget managed API — very cheap, multilingual, strong on code and structured/function-call reranking, with open weights available so you can migrate off the API later; near-tie with Qwen3 for the value slot
Where it falls shortper GPT CC-BY-NC licensing limits commercial self-hosting, while listwise processing can produce higher and less predictable latency
per Claude Peak English-retrieval quality sits a notch below Cohere and Voyage flagships, so quality-critical search products usually pay up
per Gemini Open-weights deployment requires a commercial license, and the API has higher latency overhead on extremely long contexts.
per Grok Raise general cross-domain ranking quality to close the gap with Cohere/Voyage leaders.
- 4GPT #4Claude —Gemini #4Grok —
Strong accuracy-per-dollar from a 1.5B multilingual model covering 100+ languages, with open weights and hosted access; a compelling choice when practitioners want API convenience without surrendering a future self-hosting path
+ model takes & fixes− hide details
GPT Strong accuracy-per-dollar from a 1.5B multilingual model covering 100+ languages, with open weights and hosted access; a compelling choice when practitioners want API convenience without surrendering a future self-hosting path
Gemini Implements listwise reranking to evaluate candidate documents simultaneously rather than independently, eliminating pairwise biases. Ranked fourth assuming the practitioner wants to balance Apache 2.0 open-weight flexibility with a managed API.
Where it falls shortper GPT Its hosted platform and operational track record are less mature than the leaders, and the more capable instruction-following v3 listwise model remains preview-grade
per Gemini Has a smaller developer community and less mature third-party framework integration than legacy competitors.
- 5GPT —Claude #3Gemini #5Grok —
The strongest open-weights reranker family as of 2026 (0.6B–8B, Apache 2.0), topping multilingual and code retrieval benchmarks; free to self-host and cheap via hosted APIs like DeepInfra or SiliconFlow, making it the best value at scale
+ model takes & fixes− hide details
Claude The strongest open-weights reranker family as of 2026 (0.6B–8B, Apache 2.0), topping multilingual and code retrieval benchmarks; free to self-host and cheap via hosted APIs like DeepInfra or SiliconFlow, making it the best value at scale
Gemini The premier open-weights reranking model family of 2026, offering Apache 2.0 licensing, robust performance across 100+ languages, and vision-capable multimodal variants for ranking screenshots and charts.
Where it falls shortper Claude You own the serving problem — latency and throughput tuning of a cross-encoder is on you, and hosted third-party endpoints vary in reliability; not for teams wanting a supported SLA out of the box
per Gemini High self-hosting operational complexity and resource demands, requiring substantial GPU infrastructure to achieve acceptable latency.
- 6GPT —Claude #5Gemini —Grok #4
Highest NDCG in vertical benchmarks (finance, healthcare, STEM, regulatory) with double-digit gains vs Cohere; very fast inference; enterprise-focused API with strong compliance and licensing options.
+ model takes & fixes− hide details
Grok Highest NDCG in vertical benchmarks (finance, healthcare, STEM, regulatory) with double-digit gains vs Cohere; very fast inference; enterprise-focused API with strong compliance and licensing options.
Claude The strongest newcomer — a purpose-built reranker that matches or beats incumbent APIs on public retrieval benchmarks at a fraction of the price, with an Apache-2.0 small variant as an escape hatch
Where it falls shortper Claude Young company with a short production track record and minimal enterprise ecosystem; risky as the sole relevance dependency for a large deployment
per Grok Win more decisively on broad public benchmarks beyond custom evals to move from niche leader to overall top 2.
- 7GPT #5Claude —Gemini —Grok —
Proven multilingual open-source cross-encoder with inexpensive managed serving, broad framework support, and the freedom to self-host; excellent practical value for ordinary short-query, passage-ranking pipelines
+ model takes & fixes− hide details
GPT Proven multilingual open-source cross-encoder with inexpensive managed serving, broad framework support, and the freedom to self-host; excellent practical value for ordinary short-query, passage-ranking pipelines
Where it falls shortper GPT The 1,024-token pair limit and older pointwise architecture make it materially weaker for long documents, nuanced instructions, and highest-accuracy workloads
- 8GPT —Claude —Gemini —Grok #5
Strong QA-focused retrieval accuracy with major cost/efficiency gains via NIM microservices; purpose-built for production RAG pipelines.
+ model takes & fixes− hide details
Grok Strong QA-focused retrieval accuracy with major cost/efficiency gains via NIM microservices; purpose-built for production RAG pipelines.
Where it falls shortper Grok Offer seamless deployment and API access outside NVIDIA hardware/ecosystem for broader adoption.
Rank history
Just missed the top 5
GPT ZeroEntropy zerank-2 — promising accuracy and aggressive pricing, but less independently validated and operationally proven than the top five · Pinecone rerank-v0 — convenient and fast inside Pinecone, but its 512-token limit and single-platform availability narrow its usefulness
Claude BAAI bge-reranker-v2-m3 — the long-time open-source workhorse, but superseded on quality by Qwen3 Reranker and it has no first-party API · Mixedbread Rerank — excellent open-weights quality but a much smaller API ecosystem and mindshare than the five above
Gemini BAAI BGE Reranker — highly efficient and widely supported but struggles with complex reasoning and long-context documents · Vectara Rerank — integrated exclusively into Vectara's end-to-end platform, preventing modular standalone API usage
Grok mxbai-rerank — strong RL-trained open model with managed API but lower visibility and fewer decisive benchmark wins in 2026 comparisons · BGE-reranker-v2-m3 — reliable evergreen open baseline but edged out by newer specialized models and dedicated APIs on latest evals
By model
ChatGPT
- 1.Cohere Rerank
- 2.Voyage Rerank
- 3.Jina Reranker
- 4.Mixedbread Rerank
- 5.BGE Reranker
Claude
- 1.Cohere Rerank
- 2.Voyage Rerank
- 3.Qwen3 Reranker
- 4.Jina Reranker
- 5.ZeroEntropy
Gemini
- 1.Cohere Rerank
- 2.Voyage Rerank
- 3.Jina Reranker
- 4.Mixedbread Rerank
- 5.Qwen3 Reranker
Grok
- 1.Cohere Rerank
- 2.Voyage Rerank
- 3.Jina Reranker
- 4.ZeroEntropy
- 5.NVIDIA NeMo Reranker
Common questions
What is the best reranking model api according to AI models?
Cohere Rerank leads. All 4 models rank Cohere Rerank the top pick. The current top 3: Cohere Rerank, Voyage Rerank, Jina Reranker. Ranked by asking ChatGPT, Claude, Gemini, Grok the same buying question and merging their top-5 picks, updated 2026-07-15. Source: modelsagree.com.
Which reranking model api did each AI model pick first?
ChatGPT: Cohere Rerank. Claude: Cohere Rerank. Gemini: Cohere Rerank. Grok: Cohere Rerank.
What changed in the latest reranking model api ranking?
In the latest poll (2026-07-15): Voyage Rerank climbed 1 spot, Mixedbread Rerank climbed 6 spots, Qwen3 Reranker climbed 4 spots; Jina Reranker dropped 1 spot; BGE Reranker and NVIDIA NeMo Reranker entered the ranking. The models are re-polled on demand, so this ranking moves.
How is this reranking model api ranking made?
ChatGPT, Claude, Gemini, Grok are each asked the same buying question in a fresh session with no system steering. Their top-5 answers are merged (rank 1 = 5 pts … rank 5 = 1 pt) into the consensus ranking, re-polled on demand and tracked over time.
More on how polling works: full methodology →
Cite this ranking
ModelsAgree, “Best reranking model API” — merged ranking from ChatGPT, Claude, Gemini & Grok, polled 2026-07-15. https://modelsagree.com/best/best-reranking-model-api (CC BY 4.0)
Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled on demand