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Independent Enterprise AI & Software Benchmarks

Latest AI models' performance on enterprise workloads and insights on AI for business

AIM Indices

Best model
Kev-9B
AIM System One Index 69
Fastest model
Laya
200 ms median per decision
Cheapest API model
Jev 1.13
$0.034 per 1,000 decisions
Trusted by leading media and institutions
Business Insider
DHL
European Commission
IBM
IT Brew
The Washington Post
World Economic Forum
Business Insider
DHL
European Commission
IBM
IT Brew
The Washington Post
World Economic Forum
Agentic Coding Benchmark

Compare and see the differences between AI Code editors, and CLI Agents

AI Coding
Agentic Coding Benchmark
Cloud GPU Providers

Identify the cheapest cloud GPUs for training and inference

AI Hardware
Cloud GPU Providers
GPU Concurrency Benchmark

Measure GPU performance under high parallel request load

AI Hardware
GPU Concurrency Benchmark
Multi-GPU Benchmark

Compare scaling efficiency across multi-GPU setups

AI Hardware
Multi-GPU Benchmark
AI Gateway Comparison

Analyze features and costs of top AI gateway solutions

AI Models
AI Gateway Comparison
LLM Latency Benchmark

Compare the latency of LLMs

AI Models
LLM Latency Benchmark
LLM Price Calculator

Compare LLM models input and output costs

AI Models
LLM Price Calculator
Text-to-SQL Benchmark

Benchmark LLMs' accuracy and reliability in converting natural language to SQL

AI Models
Text-to-SQL Benchmark
AI Bias Benchmark

Compare the bias rates of LLMs

AI Foundations
AI Bias Benchmark
AI Hallucination Benchmark

Evaluate hallucination rates of AI models

AI Models
AI Hallucination Benchmark
Agentic RAG Benchmark

Evaluate multi-database routing and query generation in agentic RAG

RAG
Agentic RAG Benchmark
Embedding Models Benchmark

Compare embedding models accuracy and speed

RAG
Embedding Models Benchmark
Open-Source Embedding Models Benchmark

Evaluate leading open-source embedding models accuracy and speed

RAG
Open-Source Embedding Models Benchmark
RAG Benchmark

Compare retrieval-augmented generation solutions

RAG
RAG Benchmark
Vector DB Comparison for RAG

Compare performance, pricing and features of vector DBs for RAG

RAG
Vector DB Comparison for RAG
Agentic Frameworks Benchmark

Compare latency and completion token usage for agentic frameworks

Agentic AI Frameworks
Agentic Frameworks Benchmark
Tiktok Scraping

Analyze performance of TikTok Scraper APIs

Web Data Scraping
Tiktok Scraping
Web Unblocker Benchmark

Evaluate the effectiveness of web unblocker solutions

Web Data Scraping
Web Unblocker Benchmark
Video Scrapers Benchmark

Analyze performance of Video Scraper APIs

Web Data Scraping
Video Scrapers Benchmark
AI Code Editor Comparison

Analyze performance of AI-powered code editors

AI Coding
AI Code Editor Comparison
E-commerce Scraper Benchmark

Compare scraping APIs for e-commerce data

Web Data Scraping
E-commerce Scraper Benchmark
LLM Examples Comparison

Compare capabilities and outputs of leading large language models

AI Models
LLM Examples Comparison
OCR Accuracy Benchmark

See the most accurate OCR engines and LLMs for document automation

Document Automation
OCR Accuracy Benchmark
SERP Scraper API Benchmark

Benchmark search engine scraping API success rates and prices

Web Data Scraping
SERP Scraper API Benchmark
Handwriting OCR Benchmark

Compare the OCRs in handwriting recognition

Document Automation
Handwriting OCR Benchmark
Tabular Models Benchmark

Compare tabular learning models with different datasets

AI Models
Tabular Models Benchmark
LLM Quantization Benchmark

Compare BF16, FP8, INT8, INT4 across performance and cost

AI Models
LLM Quantization Benchmark
Multimodal Embedding Models Benchmark

Compare multimodal embeddings for image–text reasoning

RAG
Multimodal Embedding Models Benchmark
LLM Inference Engines Benchmark

Compare vLLM, LMDeploy, SGLang on H100 efficiency

AI Hardware
LLM Inference Engines Benchmark
LLM Scrapers Benchmark

Compare the performance of LLM scrapers

Web Data Scraping
LLM Scrapers Benchmark
Visual Reasoning Benchmark

Compare the visual reasoning abilities of LLMs

AI Models
Visual Reasoning Benchmark
Agentic Orchestration Benchmark

Compare the orchestration performance of agentic frameworks

Agentic AI Frameworks
Agentic Orchestration Benchmark
AI Providers Benchmark

Compare the latency of AI providers

AI Foundations
AI Providers Benchmark
Multilingual Embedding Models Benchmark

Compare multilingual embedding models for RAG

RAG
Multilingual Embedding Models Benchmark
Reranker Benchmark

Compare reranker models for dense retrieval

RAG
Reranker Benchmark
Agentic LLM Benchmark

Compare LLMs across software development tasks.

AI Agents
Agentic LLM Benchmark
Computer Use Agents

Compare how strong UI grounding models are.

AI Agents
Computer Use Agents

Latest Benchmarks

AIM-Text-to-SQL Benchmark: SQL Accuracy Across 60+ LLMs

AI
Benchmark
Oct 1

SQL accuracy is the percentage of scored queries that return the reference result. Incorrect routes and references flagged as broken are excluded. A reference query is the SQL supplied as the expected answer. Each model reaches a different set of SQL questions because scoring depends on its database choices. Differences in these subsets and execution

AI
Benchmark
Oct 1

AIM-Agentic RAG Benchmark: Routing Across 11 SQL Databases

Routing accuracy is the percentage of scored questions for which the model explicitly names the correct database in its final answer. The headline uses the 184 questions flagged as difficult by both our similarity test and a jury of three LLMs. Missing explicit declarations receive no credit. Database routing findings Opus 5.5 recorded the highest

AI
Benchmark
Oct 1

AIM-Decision: Jev vs Kev vs LLMs

Decision models, also called System One models, score a fixed set of options instead of generating text token by token. We tested 19 decision models on 1,655 classification questions, such as rating a security flaw or a product recall, and ran 10 decision models on the 50 browser tasks. Classification benchmark results Browser automation success

AI
Benchmark
Oct 1

Benchmark of 80+ LLMs in Finance: Claude Opus 5.5 & GPT-6 Astra

The test set is the hard subset of the FinanceReasoning benchmark (Tang et al.), with 238 questions. Accuracy is the percentage of questions answered correctly. Numerical answers receive a 0.2% relative tolerance. Output tokens are the tokens generated across the 238 answers. Input tokens are counted separately in the cost calculation. Cost is the calculated

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Latest Insights

Top 25 Chatbot Case Studies & Success Stories

AI
Insight
Sep 30

The global chatbot market sits at roughly $11.8 billion, growing at 23% per year toward $27 billion by 2030. Most deployments fail. The bots that last are built for a single specific task and perform it better, faster, or cheaper than a human agent can at scale. We compiled a list of 25 successful chatbot

AI
Insight
Sep 30

Top 12 SEO AI Use Cases with Case Studies

As algorithms change and consumer expectations rise, it has become more challenging to compete for accessibility in search results. Conventional SEO techniques, which depend on manual research and minor updates, frequently fall behind these developments. AI-powered SEO tools address this challenge by automating complex tasks and aligning content more precisely with user intent. Explore the

AI
Open World Evaluation
Sep 30

Top 10 Drug Discovery Software

The drug discovery software market divides into three categories: computational chemistry suites for structure-based design, AI-native platforms for generative chemistry and target identification, and R&D data management systems for ELN, LIMS, synthesis tracking, data analysis, and compound registration. We compared the top 10 drug discovery platforms across features, pricing, and deployment models. Top 10 drug

AI
Insight
Sep 30

Top 50 Deep Learning Use Case & Case Studies

Deep learning uses artificial neural networks to learn from data. When trained on large, high-quality datasets, it achieves high accuracy, making it valuable wherever you have abundant data and need accurate predictions. Below are real deep learning applications across industries and business functions, with concrete examples. What are the capabilities & technologies enabled by deep

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Enterprise Tech Leaderboard

Top 3 results are shown, for more see research articles.

Tiktok Scraping
1st
Bright Data
Metric
Success Rate
Value
100 %
Metric
Success Rate
Value
99 %
Metric
Success Rate
Value
95 %
Metric
Latency
Value
2.00 s
AI Gateways
2nd
SambaNova
Metric
Latency
Value
3.00 s
AI Gateways
3rd
Together.ai
Metric
Latency
Value
11.00 s
Metric
Response Time
Value
1.75 s
Web Unlockers
2nd
Bright Data
Metric
Response Time
Value
2.38 s
Web Unlockers
3rd
Decodo
Metric
Response Time
Value
3.43 s
Amazon Scraping
1st
Bright Data
Metric
Overall
Value
Leader

Vendor
Benchmark
Metric
Value
Bright Data
Bright Data
1st
Success Rate
100 %
Apify
Apify
2nd
Success Rate
99 %
Decodo
Decodo
3rd
Success Rate
95 %
Groq
Groq
1st
Latency
2.00 s
SambaNova
SambaNova
2nd
Latency
3.00 s
Together.ai
Together.ai
3rd
Latency
11.00 s
Zyte
Zyte
1st
Response Time
1.75 s
Bright Data
Bright Data
2nd
Response Time
2.38 s
Decodo
Decodo
3rd
Response Time
3.43 s
Bright Data
Bright Data
1st
Overall
Leader

Data-Driven Decisions Backed by Benchmarks

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