Discover the best large language models for digital products

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

Explore the current LLM Benchmarks

The benchmark categories in detail

Here's exactly what we're looking at with the different categories of LLM Leaderboards

Docs

How well can the model work with large documents and knowledge bases?

CRM

How well does the model support work with product catalogs and marketplaces?

Integrate

Can the model easily interact with external APIs, services and plugins?

Marketing

How well can the model support marketing activities, e.g. brainstorming, idea generation and text generation?

Reason

How well can the model reason and draw conclusions in a given context?

Code

Can the model generate code and help with programming?

Cost

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.

Speed

The "Speed" column indicates the estimated speed of the model in requests per second (without batching). The higher the speed, the better.

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Technologie Übersicht