I Tested Gemma 4 E4B vs 31B on 50 Real Student Career Queries — The Results Surprised Me
The author tested two versions of Google's Gemma 4 model—E4B and 31B Dense—on 50 real student career queries to evaluate performance for an AI career guidance platform. Contrary to expectations, the smaller E4B model outperformed the larger 31B model on simple eligibility and emotionally ambiguous queries, while the 31B model excelled in complex, multi-constraint planning tasks. The results suggest that model selection should be task-specific, balancing cost, latency, and output quality.
- ▪The E4B model scored higher on simple eligibility checks and ambiguous or emotional queries, demonstrating strong schema compliance and proactive reasoning.
- ▪The 31B Dense model performed better on multi-constraint career planning and single-path career questions, achieving higher overall average scores.
- ▪E4B ran locally with zero cost and lower latency, while 31B operated via API with a cost of approximately ₹0.13 per query and higher response times.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3904430) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Sreejit Pradhan Posted on May 17 I Tested Gemma 4 E4B vs 31B on 50 Real Student Career Queries — The Results Surprised Me #devchallenge #gemmachallenge #gemma #opensource Gemma 4 Challenge: Write about Gemma 4 Submission I'm building PathForge AI — a career guidance platform for Indian students. The pitch is simple: AI-powered counselling for students who can't afford a human counsellor. The engineering problem underneath is not simple at all.
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