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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| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/sreejit_/i-tested-gemma-4-e4b-vs-31b-on-50-real-student-career-queries-the-results-surprised-me-kbi |
| Publication time | Sun, 17 May 2026 05:33:24 +0000 |
| Retrieval time | 2026-05-17T06:03:59.095Z |
| Last seen | 2026-05-17T06:03:59.095Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | L411n4jnR6rj |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
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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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).