Deep Hermes 3 Review: Toggling Thinking Modes and Unconventional Tests

- Authors
- Published on
- Published on
Deep Hermes 3, a model that toggles between thinking and non-thinking modes at the flick of a switch. The team dives into the nitty-gritty, praising its performance despite being rooted in Llama 3.1 rather than the more advanced Quinn. They embark on a series of unconventional tests, pushing the model to its limits. From solving Google Sheets formulas to tackling Wolfram Alpha equations, the team showcases the model's prowess in reasoning and problem-solving.
However, not all is smooth sailing for Deep Hermes 3. When tasked with coding a bouncing ball within a rotating hexagon, the model falters, showcasing its limitations in certain scenarios. Despite this setback, the team presses on, exploring the model's accuracy in identifying chemistry compounds. Deep Hermes 3 shines in this challenge, outperforming other models and delivering precise results with finesse.
As the tests continue, the team delves into the model's predictive abilities in medical symptom analysis and problem-solving in the realm of competitive exams. While Deep Hermes 3 impresses with its accuracy in certain tasks, it stumbles in others, revealing the complexities and nuances of AI models. Through a mix of praise and critique, the team paints a vivid picture of Deep Hermes 3's strengths and weaknesses, showcasing the dynamic nature of cutting-edge AI technology.

Image copyright Youtube

Image copyright Youtube

Image copyright Youtube

Image copyright Youtube
Watch Local AI Just Got Crazy Smart—And It’s Only 8B Thinking LLM! on Youtube
Viewer Reactions for Local AI Just Got Crazy Smart—And It’s Only 8B Thinking LLM!
Viewers appreciate the in-depth evaluation of small models
Channel is gaining popularity and nearing 100k subscribers
Suggestions for improving video quality such as lighting and exposure
Comparison with other models like Llama R1 Distilled and potential for larger versions of the model
Comments on the model's strengths in logical reasoning and creative output
Questions about the model's output tokens and potential for short responses
Interest in using local AI for privacy and organization data
Potential for models with agentic capabilities in powering game NPCs
Requests for information on offline version capabilities and function calling
Comparisons with other models like Yi-Coder-9B-Chat and Claude Sonnet 3.5
Related Articles

Revolutionizing AI: Quen's 32 Billion Parameter Model Dominates Coding and Math Benchmarks
Explore how a 32 billion parameter AI model from Quen challenges larger competitors in coding and math benchmarks using innovative reinforcement learning techniques. This groundbreaking approach sets a new standard for AI performance and versatility.

Unlock Flawless Transcription: Gemini's Speaker Diarization Feature
Discover the hidden gem in Gemini: speaker diarization for flawless transcription. Learn how to use Google AI Studio with Gemini for accurate speaker-separated transcripts. Revolutionize your transcription process with this powerful yet underrated feature.

Decoding Thoughts: Facebook's Brain to Quy Model Revolutionizes Non-Invasive Brain Decoding
Facebook's Brain to Quy model decodes thoughts while typing using EEG and MEG signals. Achieving 32% character error rate, it shows promise in non-invasive brain decoding for future AI applications.

Deep Seek R1: Mastering AI Serving with 545% Profit Margin
Deep Seek R1's AI system achieves a remarkable 545% profit margin, generating $560,000 daily revenue with $887,000 GPU costs. Utilizing expert parallelism and load balancing strategies, Deep Seek R1 ensures efficient GPU usage and high token throughput across nodes, setting a new standard in large-scale AI serving.