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Discover the best large language models for digital products

The monthly TIMETOACT GROUP Language Model (LLM) Benchmarks help you choose the best AI models for digital product development.

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 | September 2024

    September has been exciting! In this edition of TMETOACT GROUP LLM Benchmark we’ll talk about pushing the state of the art.

    The Highlights:

    • ChatGPT o1 models are the best, but there is a minor caveat.
    • Gemini 1.5 Pro v002 - 3rd place in the benchmark.
    • Benchmarking Qwen 2.5 and DeepSeek 2.5 - local model catching up to GPT-4 Turbo.
    • Llama 3.2 - average performance, but also with a minor caveat.
    • Trends of local LLMs over time.
    LLM Benchmarks | September 2024

    The benchmark categories in detail

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

    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

    LLM Benchmarks | August 2024
    LLM Benchmarks | July 2024
    LLM Benchmarks | June 2024
    LLM Benchmarks | May 2024
    LLM Benchmarks | April 2024

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