Benchmarks.

Fast and accurate retrieval is the backbone of the new generation of AI-native applications.
TopK is built for teams working with large volumes of data where high performance, flexibility, and cost efficiency matter.

01

Enterprise retrieval

Compare topk-embed-v1 with managed embedding providers on eight public ViDoRe v3 datasets, using page images or Markdown.

Retrieval quality versus cost

ViDoRe v3 · managed providers · upper left is better

TopKCohereVoyageGeminiMixedbread
$/1k images versus nDCG@10. Open the data table below to inspect measurements.nDCG@10455055606570$0.06$0.1$0.2$0.5$1$2$4$/1k imagesTopK (66.33)Cohere (58.23)Voyage (57.54)Gemini (56.00)Mixedbread (64.24)
View chart data and sources
Managed providerUSD / 1,000 imagesnDCG@10
topk-embed-v1 · production$0.07566.33
Cohere Embed 4≈$2.4058.23
Voyage Multimodal 3.5$0.6057.54
Gemini Embedding 2$0.1256.00
Mixedbread Wholembed V3$3.0064.24

nDCG@10 on a 0–100 scale, averaged equally across eight public ViDoRe v3 datasets. Native uses each dataset’s original query language; multilingual includes all six languages, including native.

TopK: $0.075/1,000 images. Gemini: $0.00012/image. Mixedbread: 2,000 content tokens/image at $1.50/M. Voyage: one-megapixel images at $0.60/billion pixels. Cohere is an estimate for one-megapixel images, applying AWS’s token formula (pixels ÷ 784 × 4) to Cohere’s $0.47/M image-token rate; These are billing estimates, not measured benchmark bills.

Rates: Google, Cohere, Voyage, Mixedbread (September 24, 2026). Mixedbread’s $1.50/M rate includes indexing.

02

Agentic search

Compare answer accuracy and search calls per question on BrowseComp-Plus with GPT-5 as the agent.

Agentic search

BrowseComp-Plus · GPT-5 agent · upper left is better

MixedbreadTopKqwen3-embed-8B (dense)BM25 (sparse)
Tool calls per question versus Accuracy (%). Open the data table below to inspect measurements.Accuracy (%)50607080901001014182226Tool calls per questionMixedbread (90.48%)TopK (86.87%)Qwen3 8B (71.69%)BM25 (57.59%)
View chart data and sources
MeasurementTool calls per questionAccuracy (%)
Mixedbread11.5390.48
TopK (topk-embed-v1)11.886.87
qwen3-embed-8B (dense)21.7471.69
BM25 (sparse)23.2357.59

BrowseComp-Plus results with GPT-5 as the agent. Accuracy is the percentage of correctly answered questions; search calls are averaged per question.

03

Billion documents in milliseconds

Predictable latency at scale with filtered or unfiltered queries.

Query latency

p50p99
LOWER IS BETTER
View latency data
Documentsp50 · No filterp99 · No filter
10M15.5 ms17 ms
100M31.2 ms34.8 ms
1B52.9 ms61.8 ms

Latency measured on a production-config cluster with randomly generated documents and queries.

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