| --- |
| license: gemma |
| license_name: gemma-terms-of-use |
| license_link: https://ai.google.dev/gemma/terms |
| base_model: google/gemma-3-4b-it |
| pipeline_tag: text-generation |
| library_name: gguf |
| language: |
| - en |
| tags: |
| - gemma3 |
| - gguf |
| - text-only |
| - ollama |
| - breadcrumb |
| --- |
| |
| Google's Gemma 3 4B, as Ollama builds it, with the picture-reading part taken out. |
| The text weights are the same bytes. It writes text. It cannot look at an image. |
|
|
| ## What it is |
|
|
| This is Ollama's own `gemma3:4b` — the Q4_K_M build of `google/gemma-3-4b-it` — with the |
| vision tower and the multimodal projection removed and nothing else changed. |
|
|
| - Source file: the model layer of `gemma3:4b`, |
| sha256 `aeda25e63ebd698fab8638ffb778e68bed908b960d39d0becc650fa981609d25`, |
| 3,338,792,448 bytes. |
| - What came out: 439 tensors whose names begin `v.` (the SigLIP vision tower) or `mm.` |
| (the multimodal input projection), and 9 metadata keys — `gemma3.mm.tokens_per_image` |
| and the eight `gemma3.vision.*` keys. |
| - What stayed: all 444 text tensors, byte for byte. Same names, same ggml quantization |
| types, same shapes, same bytes. Nothing was requantized, converted, retrained or |
| fine-tuned. The tokenizer is untouched, all 262,145 entries, so token numbers do not |
| move and the model writes the same words. |
| - What was added: one metadata key, `general.description`, carrying the notice that this |
| file is a modified Gemma file. |
| - Result: 2,498,332,864 bytes, |
| sha256 `199388f8f8cbec06b80bd63b0b1a774103e00c993c107bf1d480e58047420532`. |
|
|
| The template and the sampling parameters are the ones Ollama ships with `gemma3:4b`, |
| unchanged: stop `<end_of_turn>`, temperature 1, top_k 64, top_p 0.95. |
|
|
| ## Why |
|
|
| [Breadcrumb](https://innerloop.works/breadcrumb), by Innerloop, uses this model to give screens, chapters and meetings short names. It only |
| ever sends it text. The vision tower was 840 MB of weights that were read off disk, |
| paged in and held in memory for work that never happened. |
|
|
| Measured on the same machine, one model resident at a time, with `footprint` against the |
| running `llama-server`: |
|
|
| | | on disk | held while answering | |
| |---|---|---| |
| | `gemma3:4b` | 3.3 GB | 4.28 GB | |
| | this model | 2.5 GB | 2.73 GB | |
|
|
| That is about 1.6 GB less memory while it is working, and 0.8 GB less disk. On an 8 GB |
| Mac that is the difference between naming a screen and swapping. |
|
|
| The names it writes are the same names. On 300 pinned items from a real store — 150 |
| screen moments, 75 chapters, 75 meetings — this file and `gemma3:4b` wrote 300 identical |
| titles out of 300, at the same settings, and both were stable across a second pass. |
|
|
| ## It cannot see |
|
|
| This is a text-only model. There is no vision tower in the file and no projector layer in |
| the manifest. `ollama show` reports one capability, `completion`, where `gemma3:4b` |
| reports `completion` and `vision`. If you send it an image it has nothing to look at. |
| If you need Gemma 3 to read pictures, use `gemma3:4b` instead. |
|
|
| ## Gemma notice |
|
|
| Gemma is provided under and subject to the Gemma Terms of Use found at |
| ai.google.dev/gemma/terms |
|
|
| This distribution contains a modified Gemma file. The full Gemma Terms of Use, as last |
| modified April 1, 2026, travel with the model: the LICENSE file in this repository is that complete copy, and NOTICE carries the modification notice. |
|
|
| Use of this model is subject to Google's Gemma Prohibited Use Policy at |
| ai.google.dev/gemma/prohibited_use_policy. That policy is part of the Gemma Terms and |
| applies to you whether you got this model from us or from anywhere else. If you pass this |
| model on, or anything you build from it, you pass these terms on with it and you tell the |
| people you pass it to that the Gemma use restrictions apply. |
|
|
| Google claims no rights in what you generate with it. |
|
|
| Everything in this distribution that is not Gemma is © Innerloop, [innerloop.works](https://innerloop.works). |
|
|
| ## How to verify it yourself |
|
|
| You do not have to take our word that only the vision parts came out. The check needs |
| nothing but a GGUF reader. |
|
|
| 1. Get Ollama's `gemma3:4b` and find its model layer in your blob store. It should hash |
| to `aeda25e63ebd698fab8638ffb778e68bed908b960d39d0becc650fa981609d25`. |
| 2. Get this model and find its model layer. It should hash to |
| `199388f8f8cbec06b80bd63b0b1a774103e00c993c107bf1d480e58047420532` and be |
| 2,498,332,864 bytes. |
| 3. Open both with a GGUF reader and list the tensors. The original has 883 tensors and |
| this one has 444 tensors. Every one of the 439 missing tensors has a name beginning |
| `v.` or `mm.`. Nothing else is missing. |
| 4. The 444 that remain are `token_embd.weight`, `output_norm.weight`, and thirteen |
| tensors for each of the 34 blocks: `attn_q.weight`, `attn_k.weight`, `attn_v.weight`, |
| `attn_output.weight`, `attn_q_norm.weight`, `attn_k_norm.weight`, `attn_norm.weight`, |
| `post_attention_norm.weight`, `ffn_gate.weight`, `ffn_up.weight`, `ffn_down.weight`, |
| `ffn_norm.weight`, `post_ffw_norm.weight`. By quantization: 205 Q4_K, 34 Q6_K, |
| 205 F32, the same counts as in the original's text half. |
| 5. For each of those 444, compare the ggml type, the shape, the byte count and the |
| sha256 of the tensor's own bytes against the same tensor in the original. All 444 |
| match. Any single mismatch means the weights were touched, and they were not. |
| 6. The metadata: 27 keys here against 35 in the original. The 9 that are gone are the |
| vision keys listed above. One key is new, `general.description`, which says the file |
| was modified. `general.architecture` is still `gemma3`, and the tokenizer keys are |
| identical. |
|
|
| The script that does the surgery lives in a private repository, so the recipe is written |
| out above rather than linked. It is short enough to re-implement: copy every tensor whose |
| name does not start with `v.` or `mm.`, copy every metadata key that does not start with |
| `gemma3.vision.` or `gemma3.mm.`, add `general.description`, write the file. Then hash |
| what you wrote. If you get `199388f8…` you have reproduced it exactly. |
|
|
| ## What we did not do |
|
|
| No fine-tuning. No requantization. No distillation. No change to the tokenizer, the chat |
| template or the sampling defaults. No system prompt. This is the same model, minus a part |
| it was not being asked to use. |
|
|
|
|
| ## Get it |
|
|
| - Ollama: `ollama run innerloop/gemma3-4b-text` (the same file, published at https://ollama.com/innerloop/gemma3-4b-text) |
| - This repository: the GGUF is `gemma-3-4b-it-text-Q4_K_M.gguf`, 2,498,332,864 bytes, sha256 `199388f8f8cbec06b80bd63b0b1a774103e00c993c107bf1d480e58047420532`. |
|
|
