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What this is
Gemma is Google's family of open-weight models derived from Gemini research. shipfeed tracks Gemma releases, weights, fine-tunes, and local-inference support.
mtmd: fix Gemma 4 unified FPE (#24088) macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu arm64 (CPU) Ubuntu…
Google DeepMind released Gemma 4, a family of open-source AI models including 26B MoE and 31B Dense variants, outperforming larger competitors and aimed at advanced reasoning and agentic workflows.
Gemma 4 was launched by Google under an Apache 2.0 license, marking a significant open-model release focused on reasoning, agentic workflows, multimodality, and on-device use. It outperforms models 10x larger and has…
EmbeddingGemma 2: an open, lightweight multimodal embedding model blog.google
Google: Google DeepMind launches EmbeddingGemma 2, a 740M-parameter model to map code, images, video, and audio in a shared embedding space, under an Apache 2.0 license — EmbeddingGemma 2 is the most capable…
Nimbus builds production AI systems — internal tools, customer agents, retrieval pipelines — combining humans and AI end-to-end. From scoped pilot to production in 4–8 weeks.
The Register: Nvidia says its Groq 3 LPX racks delivered 3,400 tokens per second in an Artificial Analysis benchmark running Gemma 4 31B with a 100,000-token input sequence — Nvidia's $20 billion bet on Groq's…
Google Deepmind's Gemma 4 12B is an open-source model that processes text, images, and audio natively and runs on laptops with just 16 GB of RAM. It nearly matches the twice-as-large 26B model in benchmarks and ships…
Release v5.10.1 v5.10.0 was yanked as we publish on a corrupted branch. Sorry everyone, this happens when we rush a release!!! New Model additions Gemma4 unified+ Gemma4 MTP Gemma 4 12B Unified is an encoder-free…
An eventful month with one flagship release after another
Release v5.8.0 New Model additions DeepSeek-V4 DeepSeek-V4 is the next-generation MoE (Mixture of Experts) language model from DeepSeek that introduces several architectural innovations over DeepSeek-V3. The…
vLLM v0.19.0 Highlights This release features 448 commits from 197 contributors (54 new)! Gemma 4 support: Full Google Gemma 4 architecture support including MoE, multimodal, reasoning, and tool-use capabilities…
Gemma 4 Effective 2B (E2B) ``` ollama run gemma4:e2b ``` Effective 4B (E4B) ``` ollama run gemma4:e4b ``` 26B (Mixture of Experts model with 4B active parameters) ``` ollama run gemma4:26b ``` 31B (Dense) ``` ollama…
GLM-4.7 and MiniMax M2.1 open-weight model releases highlight day-0 ecosystem support, coding throughput, and agent workflows, with GLM-4.7 achieving a +9.5% improvement over GLM-4.6 and MiniMax M2.1 positioned as an…
Google DeepMind released EmbeddingGemma 2, a 740M-parameter open multimodal embedding model that maps text, code, images, video, and audio into a shared 768-dimensional space. It is available under Apache 2.0 and…
Instead of training a new model from scratch, Google DeepMind retrofitted Gemma 4 into a diffusion model using less than 10 percent of the original training budget. DiffusionGemma generates 256 tokens in parallel…
Hi HN,I built a specialized inference engine for running 4-bit Gemma 4 26B-A4B-IT on any M-series Mac using about 2 GB of RAM. It is called TurboFieldfare and is written in Swift and Metal.I have always adored…
The viability of orbital data centers hosting the largest and most capable large language models (LLMs) remains hotly contested. But enormous deployments that require thousands of GPUs aren’t the only way LLMs might…
Google released DiffusionGemma, a 26-billion-parameter model that generates text not token by token but through diffusion, similar to how image AI turns noise into a picture. According to Nvidia, it hits about 1,000…
The new Diffusion Gemma open model generates text in parallel — not one token at a time — and is optimized to run on the NVIDIA RTX PRO platform, NVIDIA DGX Spark systems and GeForce RTX GPUs.
Google DeepMind launched Gemma 4 12B, a dense, multimodal, encoder-free model capable of running natively on consumer laptops with 16GB of RAM.
Nimbus builds production AI systems — internal tools, customer agents, retrieval pipelines — combining humans and AI end-to-end. From scoped pilot to production in 4–8 weeks.
From Gemma 4 to DeepSeek V4, How New Open-Weight LLMs Are Reducing Long-Context Costs
Release v5.5.0 New Model additions Gemma4 Gemma 4 is a multimodal model with pretrained and instruction-tuned variants, available in 1B, 13B, and 27B parameters. The architecture is mostly the same as the previous…
Hey HN, Henry & Roman here from Cactus.A small, on-device model is fast and private, but sometimes wrong, but frontier models are getting expensive pretty fast. So, we post-trained Gemma 4 E2B post-trained to know when…
mtmd: enable non-causal vision for gemma 4 unified (#24082) macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu…
What's Changed models: add support for gemma4-12b by @pdevine in https://github.com/ollama/ollama/pull/16457 Full Changelog: https://github.com/ollama/ollama/compare/v0.30.2...v0.30.3
Gemma 4 MTP (Multi-token Processing) for the MLX runner Gemma 4 MTP speculative decoding is now supported on Macs. This can give over a 2x speed increase for the Gemma 4 31B model on coding tasks. ``` ollama run…