Comparing SLMs and LLMs with similarity metrics @juliensimonfr
Comparing SLMs and LLMs with similarity metrics  @juliensimonfr
Uploaded April 2025 | Updated September 2026, 2 weeks ago
In this video, we build a model-testing web application with Arcee Conductor (arcee.ai/product/arcee-conductor) and Gradio. We also implement several similarity metrics (Jaccard, Cosine Similarity, Levenshtein, and Semantic Similarity), as well as a user feedback mechanism. Then, we run a few examples with SLMs and LLMs, showing how small models can generate answers that are extremely similar to those of much larger models.

Arcee Conductor (arcee.ai/product/arcee-conductor) is an inference platform that intelligently routes any query to the best model, efficiently delivering precise and cost-effective results for any task.

If you’d like to understand how Arcee AI can help your organization build scalable and cost-efficient AI solutions, don't hesitate to contact sales@arcee.ai or book a demo at arcee.ai/book-a-demo.

⭐️⭐️⭐️ Don't forget to subscribe to be notified of future videos. You can also follow me on Medium at julsimon.medium.com or Substack at https://julsimon.substack.com. ⭐️⭐️⭐️

* Arcee Conductor: conductor.arcee.ai
* Arcee Conductor product page: arcee.ai/product/arcee-conductor
* Code: gitlab.com/juliensimon/arcee-demos/-/tree/main/conductor-ab-testing
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Julien Simon |

Comparing SLMs and LLMs with similarity metrics

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