r/LocalLLaMAJun 3, 2026, 23:57 UTC+8

google/gemma-4-12B on Hugging Face

google/gemma-4-12B · Hugging Face

Google DeepMind released Gemma 4 open-weight models in five sizes, with the 12B variant supporting text, image, and audio input, instruction-tuned and pre-trained variants, native system prompts, function calling, and a context window of up to 256K tokens.

Why it matters: Gemma 4 clears HKR-H/K/R: open weights, multimodal input, and 256K context make it more than a routine update. Missing benchmarks, license detail, and fuller official context keep it in the 78–84 band.

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Gemma 4 12B has an aggressive spec sheet, but the source only supports a title-level read. The summary claims five sizes, a 12B model, text-image-audio input, instruction-tuned and pre-trained variants, native system prompts, function calling, and up to 256K tokens. The Reddit body is blocked by a 403, so license terms, benchmarks, weight format, KV-cache cost, and the audio path are not visible.

My read: Google is pushing Gemma from “nice developer model” toward a local agent base. A 12B model with 256K context directly pressures Qwen’s open models and Meta’s smaller Llama line. The catch is local inference. Multimodal long context looks great in a launch card and gets ugly fast in VRAM. Without MMLU, SWE-bench, MMMU, or throughput numbers, don’t treat this as Gemini capability simply handed down.

Source: r/LocalLLaMA · reddit.com
Published: Jun 3, 2026, 23:57 UTC+8 · Jun 3, 2026