{"slug": "gemma-4-12b", "name": "Gemma 4 12B", "category": "ai", "category_name": "AI models and assistants", "description": "", "recommenders": 3, "commenters": 5, "warners": 2, "score": 0.368, "rising": 3.0, "first": "2026-06-29", "latest": "2026-09-21", "why": "I use Gemma 4 12B in the 4-bit quantization for all sorts of vision tasks (image sorting, classification, description).", "why_is_quote": true, "has_verdict": false, "sentiment": {"recommend": 3, "neutral": 0, "compare": 0, "warn": 2}, "spark": [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0], "listed": true, "loved": [], "caveat": "", "short_quote": "I use Gemma 4 12B in the 4-bit quantization for all sorts of vision tasks (image sorting, classification, description).", "icon": true, "domain": null, "github_repo": null, "official_url": "https://ai.google.dev/gemma", "pricing": "", "aliases": ["Gemma 4 12B", "Gemma 4 12b"], "verdict": null, "praise": [{"label": "", "summary": "", "quotes": [{"id": 796552416, "item_id": 49784526, "url": "https://news.ycombinator.com/item?id=49784526", "by": "faangguyindia", "date": "2026-09-21", "stance": "recommend", "quote": "On Gemma 4 12B, I am getting 220 ms per move", "excerpt": "On Gemma 4 12B, I am getting 220 ms per move or QS. I used it to play the Snake game locally: prompt_eval=244 ms wall=245 ms schema_cache=hit generated=0 Move limit reached after 200 moves: score=16, length=19. So, if a 12B dense model can offer this latency on a local old PC, then definitely you can scale it up with more powerful machines and get even lower latency.", "context": "runs on an old local PC", "use_case": "local Snake game playing", "switched_from": "", "story": "Kev: Tiny Jev-like family of decision models built on top of Qwen3.5"}, {"id": 792919632, "item_id": 49557477, "url": "https://news.ycombinator.com/item?id=49557477", "by": "codazoda", "date": "2026-09-03", "stance": "recommend", "quote": "Yesterday I did have success with Gemma-4-12b with 128k context.", "excerpt": "I want a Qwen 3.8 27B hosted locally but I don't quite have the RAM for it. And, I don't want to buy the RAM until I prove I can use it. Yesterday I did have success with Gemma-4-12b with 128k context. It fits in my RAM and it's relatively fast on my hardware. I had to give it prompts that are quite a bit different from the way I use foundation models, but I did get it to work quite well. I feel like I could learn it", "context": "", "use_case": "local LLM", "switched_from": "", "story": "Qwen 3.8 27B available on Cerebras at 1500 tokens/s"}, {"id": 788879824, "item_id": 49304989, "url": "https://news.ycombinator.com/item?id=49304989", "by": "SwellJoe", "date": "2026-08-14", "stance": "recommend", "quote": "I use Gemma 4 12B in the 4-bit quantization for all sorts of vision tasks (image sorting, classification, description).", "excerpt": "I use Gemma 4 12B in the 4-bit quantization for all sorts of vision tasks (image sorting, classification, description). It's also good for the same sorts of things for text (but there are probably better/faster models for text, 12B just happens to excel at vision tasks). The Qwen 9B is also very good for those tasks. If you need to do any kind of \"search the web, grab some data, do some kind of action\" tasks, these s", "context": "", "use_case": "local vision tasks", "switched_from": "", "story": "Qwen3.8-27B"}]}], "caveats": [{"label": "", "summary": "", "quotes": [{"id": 779754049, "item_id": 48734628, "url": "https://news.ycombinator.com/item?id=48734628", "by": "automajicly", "date": "2026-06-30", "stance": "warn", "quote": "seems more like a downgrade than an upgrade", "excerpt": "I have a M1 Macbook Pro...with only 16gb and I struggled with Qwens2.5-14b trying to do large projects. I loved Qwen but I had to try and do something different. So I switched to Gemma4-12b which looking at it now, seems more like a downgrade than an upgrade.Can you refer me to any Qwen coding models that wont choke my poor 16gb and also connect contextually? I need that context. I love the laser point focus, but I n", "context": "M1 MacBook Pro with 16GB", "use_case": "local coding", "switched_from": "Qwen2.5-14B", "story": "Qwen 3.6 27B is the sweet spot for local development"}, {"id": 779559792, "item_id": 48722487, "url": "https://news.ycombinator.com/item?id=48722487", "by": "sleepyeldrazi", "date": "2026-06-29", "stance": "warn", "quote": "it just starts confusing itself really quickly when I give it coding tasks. And quickly starts failing tool calls.", "excerpt": "I need to ask, since I have desperately wanted to make Gemma 4 12B work, but im not sure if its the quant (i usually up it to q8, which is a lot higher than iq4_nl that i use for 3.6 27B) or the model itself, but it just starts confusing itself really quickly when I give it coding tasks. And quickly starts failing tool calls. I really want to have a model that i can run locally on my 24gb m4 pro mbp for when i don't ", "context": "runs a 24GB M4 Pro MacBook Pro and a 3090", "use_case": "local coding agent", "switched_from": "", "story": "Qwen 3.6 27B is the sweet spot for local development"}]}], "who": [{"by": "faangguyindia", "context": "runs on an old local PC", "url": "https://news.ycombinator.com/item?id=49784526", "date": "2026-09-21"}], "tags": [], "use_cases": ["local snake game playing", "local workloads", "local llm", "local vision tasks", "local coding", "local coding agent"], "compared": [{"slug": "qwen-3-8", "name": "Qwen 3.8", "co": 2, "switched_from": 0, "switched_to": 0}], "makers": [], "threads": [{"url": "https://news.ycombinator.com/item?id=48721903", "title": "Qwen 3.6 27B is the sweet spot for local development", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=49783999", "title": "Kev: Tiny Jev-like family of decision models built on top of Qwen3.5", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49672966", "title": "Ask HN: What default model do you use and why?", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49554520", "title": "Qwen 3.8 27B available on Cerebras at 1500 tokens/s", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=49299684", "title": "Qwen3.8-27B", "mentions": 1}], "sentiment_by_month": {"2025-11": {}, "2025-12": {}, "2026-01": {}, "2026-02": {}, "2026-03": {}, "2026-04": {}, "2026-05": {}, "2026-06": {"warn": 2}, "2026-07": {}, "2026-08": {"recommend": 1}, "2026-09": {"recommend": 2}, "2026-10": {}}, "quotes": [{"id": 796552416, "item_id": 49784526, "url": "https://news.ycombinator.com/item?id=49784526", "by": "faangguyindia", "date": "2026-09-21", "stance": "recommend", "quote": "On Gemma 4 12B, I am getting 220 ms per move", "excerpt": "On Gemma 4 12B, I am getting 220 ms per move or QS. I used it to play the Snake game locally: prompt_eval=244 ms wall=245 ms schema_cache=hit generated=0 Move limit reached after 200 moves: score=16, length=19. So, if a 12B dense model can offer this latency on a local old PC, then definitely you can scale it up with more powerful machines and get even lower latency.", "context": "runs on an old local PC", "use_case": "local Snake game playing", "switched_from": "", "story": "Kev: Tiny Jev-like family of decision models built on top of Qwen3.5"}, {"id": 794775284, "item_id": 49673455, "url": "https://news.ycombinator.com/item?id=49673455", "by": "codazoda", "date": "2026-09-12", "stance": "neutral", "quote": "I'm trying to use Gemma 4 12b for some workloads but I haven't mastered the model yet.", "excerpt": "I use Sonnit for my personal work and Opus for my professional work. For my personal stuff, I'm on a small $20 plan, so I need to use tokens conservatively. I was very rarely exceeding limits until I built a Dark Software Factory. It's not as efficient at token use. So, I use Sonnit over Opus here. At work I have a $100 plan that I rarely exceed so I use Opus. I have access to Fable too, and I did use it a lot while ", "context": "", "use_case": "local workloads", "switched_from": "", "story": "Ask HN: What default model do you use and why?"}, {"id": 792919632, "item_id": 49557477, "url": "https://news.ycombinator.com/item?id=49557477", "by": "codazoda", "date": "2026-09-03", "stance": "recommend", "quote": "Yesterday I did have success with Gemma-4-12b with 128k context.", "excerpt": "I want a Qwen 3.8 27B hosted locally but I don't quite have the RAM for it. And, I don't want to buy the RAM until I prove I can use it. Yesterday I did have success with Gemma-4-12b with 128k context. It fits in my RAM and it's relatively fast on my hardware. I had to give it prompts that are quite a bit different from the way I use foundation models, but I did get it to work quite well. I feel like I could learn it", "context": "", "use_case": "local LLM", "switched_from": "", "story": "Qwen 3.8 27B available on Cerebras at 1500 tokens/s"}, {"id": 788879824, "item_id": 49304989, "url": "https://news.ycombinator.com/item?id=49304989", "by": "SwellJoe", "date": "2026-08-14", "stance": "recommend", "quote": "I use Gemma 4 12B in the 4-bit quantization for all sorts of vision tasks (image sorting, classification, description).", "excerpt": "I use Gemma 4 12B in the 4-bit quantization for all sorts of vision tasks (image sorting, classification, description). It's also good for the same sorts of things for text (but there are probably better/faster models for text, 12B just happens to excel at vision tasks). The Qwen 9B is also very good for those tasks. If you need to do any kind of \"search the web, grab some data, do some kind of action\" tasks, these s", "context": "", "use_case": "local vision tasks", "switched_from": "", "story": "Qwen3.8-27B"}, {"id": 779754049, "item_id": 48734628, "url": "https://news.ycombinator.com/item?id=48734628", "by": "automajicly", "date": "2026-06-30", "stance": "warn", "quote": "seems more like a downgrade than an upgrade", "excerpt": "I have a M1 Macbook Pro...with only 16gb and I struggled with Qwens2.5-14b trying to do large projects. I loved Qwen but I had to try and do something different. So I switched to Gemma4-12b which looking at it now, seems more like a downgrade than an upgrade.Can you refer me to any Qwen coding models that wont choke my poor 16gb and also connect contextually? I need that context. I love the laser point focus, but I n", "context": "M1 MacBook Pro with 16GB", "use_case": "local coding", "switched_from": "Qwen2.5-14B", "story": "Qwen 3.6 27B is the sweet spot for local development"}, {"id": 779559792, "item_id": 48722487, "url": "https://news.ycombinator.com/item?id=48722487", "by": "sleepyeldrazi", "date": "2026-06-29", "stance": "warn", "quote": "it just starts confusing itself really quickly when I give it coding tasks. And quickly starts failing tool calls.", "excerpt": "I need to ask, since I have desperately wanted to make Gemma 4 12B work, but im not sure if its the quant (i usually up it to q8, which is a lot higher than iq4_nl that i use for 3.6 27B) or the model itself, but it just starts confusing itself really quickly when I give it coding tasks. And quickly starts failing tool calls. I really want to have a model that i can run locally on my 24gb m4 pro mbp for when i don't ", "context": "runs a 24GB M4 Pro MacBook Pro and a 3090", "use_case": "local coding agent", "switched_from": "", "story": "Qwen 3.6 27B is the sweet spot for local development"}]}