
TIMETOACT GROUP Austria is one of the leading experts in the field of applied research on generative AI for businesses.
Our research findings flow directly into product development, enabling us to set the highest standards when implementing AI-powered applications for businesses.
Based on real benchmark data from our own software products, we re-evaluate each month the performance of different LLM models in addressing specific challenges. We examine specific categories such as document processing, CRM integration, external integration, marketing support, and code generation.
LLM Benchmarks | February 2025
Highlights:
AI coding tests imported into benchmark
OpenAI: o3-mini and GPT-4.5
Anthropic: Claude 3.7 with reasoning and without
Qwen: QwQ 32B, Qwen Max, Qwen Plus
Crisis of OpenAI SDK as a common standard for LLM APIs
Insights from the Enterprise RAG Challenge

The benchmark categories in detail
How well can the model work with large documents and knowledge bases?
How well does the model support work with product catalogs and marketplaces?
Can the model easily interact with external APIs, services and plugins?
How well can the model support marketing activities, e.g. brainstorming, idea generation and text generation?
How well can the model reason and draw conclusions in a given context?
Can the model generate code and help with programming?
The estimated cost of running the workload. For cloud-based models, we calculate the cost according to the pricing. For on-premises models, we estimate the cost based on GPU requirements for each model, GPU rental cost, model speed, and operational overhead.
The "Speed" column indicates the estimated speed of the model in requests per second (without batching). The higher the speed, the better.
Archive
Curious about how the scores have evolved? Here you can find all links to previously published leaderboards

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