Gemma 4 Soft Tokens: The Rise and Fall of 16x16 Words ⚡👀
Gemma 4 introduces significant advancements in vision capabilities compared to its predecessors. The model now utilizes 48x48 soft tokens for image processing, moving away from the previous 16x16 patch representation. This change enhances the integration of visual information within the model's architecture.
- ▪Gemma 4 features native vision capabilities across all its variants.
- ▪The model processes images using 48x48 soft tokens, fundamentally changing visual information representation.
- ▪The introduction of the Vision Transformer (ViT) allowed transformers to be applied to images effectively.
DEV.to (Top) files mainly under programming. We currently carry 4,924 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/eteimz/gemma-4-soft-tokens-the-rise-and-fall-of-16x16-words-5a7c |
| Publication time | Sun, 24 May 2026 22:54:37 +0000 |
| Retrieval time | 2026-05-24T23:07:34.930Z |
| Last seen | 2026-05-24T23:07:34.930Z |
| 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 | E6QxiBpfcPmw |
| 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 |
Rights status (four layers)
WeSearch handling by dimension
| 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 === 673619) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Youdiowei Eteimorde Posted on May 24 Gemma 4 Soft Tokens: The Rise and Fall of 16x16 Words ⚡👀 #devchallenge #gemmachallenge #gemma Gemma 4 Challenge: Write about Gemma 4 Submission This is a submission for the Gemma 4 Challenge: Write About Gemma 4 The road to vision capabilities in the Gemma family has been an interesting one. The first and second generations of Gemma models did not include native vision support.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
Discussion
0 commentsMore from DEV.to (Top)
