Life & fun · alternatives · 2026
24 alternatives to Cactus Hybrid: We taught Gemma 4 to know when it's wrong
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 it's wrong. Every response comes with a confidence score between 0 and 1. Developers can accept the on-device when it's high, hand off to a bigger cloud model when it's low. By routing only 15-35% of queries to Gemini 3.1 Flash-Lite, Gemma-4-E2B matches Gemini 3.1 Flash-Lite on most benchmarks. - ChartQA: 15-20% - LibriSpeech: 25-30% - MMBench, GigaSpeech, MMAU: 30-35% -…
Cactus Hybrid is a hybrid AI system that pairs a small on-device model with larger cloud models to balance speed, privacy, and accuracy. The on-device model, based on post-trained Gemma 4, provides a confidence score… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Gemma 2▲279Lightweight, state-of-the-art open models from Google
2024 · blog.google · its alternatives →
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Google Gemma 4▲437Google's most intelligent open models to date
Apr 2026 · blog.google · its alternatives →
- 3
Hey HN, Henry and Roman here - we've been building a cross-platform framework for deploying LLMs, VLMs, Embedding Models and TTS models locally on smartphones. Ollama enables deploying LLMs models locally on laptops and edge severs, Cactus enables deploying on phones. Deploying directly on phones facilitates building AI apps and agents capable of phone use without breaking privacy, supports real-time inference with no latency, we have seen personalised RAG pipelines for users and more. Apple and Google actively went into local AI models recently with the launch of Apple Foundation Frameworks…
2025 · github.com · its alternatives →
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- 5
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
Aug 2026 · cactuscompute.com · its alternatives →
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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 on-device AI. It feels like magic that you can run a powerful NN on your Mac or iPhone. So I wanted to push the limits a bit and run a model whose weights don’t fit in memory. The model’s 4-bit quantized weights occupy roughly 14 GB, which makes running it with conventional inference tools almost impossible on an 8 GB or even 16 GB Mac once the OS, applications, and KV cache are…
Jul 2026 · github.com · its alternatives →
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Gemma Gem is a Chrome extension that loads Google's Gemma 4 (2B) through WebGPU in an offscreen document and gives it tools to interact with any webpage: read content, take screenshots, click elements, type text, scroll, and run JavaScript. You get a small chat overlay on every page. Ask it about the page and it (usually) figures out which tools to call. It has a thinking mode that shows chain-of-thought reasoning as it works. It's a 2B model in a browser. It works for simple page questions and running JavaScript, but multi-step tool chains are unreliable and it sometimes ignores its tools…
Apr 2026 · github.com · its alternatives →
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Gemma 3n▲199Run powerful multimodal AI right on your phone
2025 · developers.googleblog.com · its alternatives →
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About six months ago, I started working on a project to fine-tune Whisper locally on my M2 Ultra Mac Studio with a limited compute budget. I got into it. The problem I had at the time was I had 15,000 hours of audio data in Google Cloud Storage, and there was no way I could fit all the audio onto my local machine, so I built a system to stream data from my GCS to my machine during training. Gemma 3n came out, so I added that. Kinda went nuts, tbh. Then I put it on the shelf. When Gemma 4 came out a few days ago, I dusted it off, cleaned it up, broke out the Gemma part from the Whisper…
Apr 2026 · github.com · its alternatives →
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
May 2026 · github.com · its alternatives →
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- 12IR
2023 · sagittarius.greg.technology · its alternatives →
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GPT-6 Sol & Luna▲350Frontier AI intelligence, now at half the price
Sep 2026 · openai.com · its alternatives →
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Qwen3.5 Small▲3550.8B-9B native multimodal w/ more intelligence, less compute
Mar 2026 · huggingface.co · its alternatives →
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Your next breakthrough, accelerated by AI
Mar 2026 · cortexresearch.co.uk · its alternatives →
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TxGemma▲134AI models for faster drug development
2025 · developers.googleblog.com · its alternatives →
- 17
Hey HN! I'm Baha, creator of Mysti. The problem: I pay for Claude Pro, ChatGPT Plus, and Gemini but only one could help at a time. On tricky architecture decisions, I wanted a second opinion. The solution: Mysti lets you pick any two AI agents (Claude Code, Codex, Gemini) to collaborate. They each analyze your request, debate approaches, then synthesize the best solution. Your prompt → Agent 1 analyzes → Agent 2 analyzes → Discussion → Synthesized solution Why this matters: each model has different training and blind spots. Two perspectives catch edge cases one would miss. It's like pair…
Dec 2025 · github.com · its alternatives →
- 18
We wrote our inference engine on Rust, it is faster than llama cpp in all of the use cases. Your feedback is very welcomed. Written from scratch with idea that you can add support of any kernel and platform.
2025 · github.com · its alternatives →
- 19
I wanted to know how fast a 26B mixture-of-experts model could run on a desktop CPU with no GPU. Got ~40 tok/s single-stream (lossless) and ~124 batched. The surprising part was the byte budget: for this model you compress the output head (32% of per-token bytes), not the experts (16%). The writeup has the bandwidth roofline and the dead-ends; the repo has the reproducible recipe. Happy to answer questions. Repo: https://github.com/arun-prasath2005/gemma4-cpu-moe
Jun 2026 · apeg.dev · its alternatives →
- 20PT
Gemma 4 E2B generating Excalidraw diagrams from text prompts, running entirely in desktop Chrome via WebGPU. KV cache compressed 2.4× using TurboQuant
Apr 2026 · teamchong.github.io · its alternatives →
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Fine-tuned Gemma 2: 2B model for Kazakh Instructions (SLLM)
2025 · huggingface.co · its alternatives →
- 22
I made my first macOS utility app that ships with a bundled Gemma 4 model, specifically the Gemma E4B one. It made my app DMG have 5.3 GB in size, but I think it is a small size for the power that this free local model can provide. It runs fine on CPU, but can also run on Apple Silicon GPU, although I did not notice any performance improvements with GPU (tested on a M5 chip). I think these local lightweight and multimodal models will open multiple possibilities for new software tools where privacy is essential.
May 2026 · snapname.app · its alternatives →
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Viberia▲146Hey HN, This is my take on the agent harness. Everything on an isometric map. Agents are grouped into "buildings" that run in a sequence or a loop; e.g., the CodeForge has an agent that writes a PRD, another one that implements, and a third that reviews. Everything is customizable, you build your own buildings/teams however you want. It's a Tauri app, really light (about 8x less energy than the closest competitor I benchmarked, so it actually runs from a coffee shop on battery). It's macOS only for now, but ping me if you are willing to test the Windows or Linux version. I've been…
May 2026 · getviberia.com · its alternatives →
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thisorthis.ai▲135Hey HN — I'm Parth, I built thisorthis.ai because I was tired of copy-pasting the same prompt across ChatGPT, Claude, and Gemini tabs to figure out which model actually gave the best answer. What it does: You type one prompt, pick 2–6 models (we support 47 text models and several image models across OpenAI, Anthropic, Google, xAI, Meta, Amazon, Mistral, Cohere, AI21), and see every response side-by-side. There's also a feature called SmartPick that uses an LLM evaluator to score each response on Clarity, Accuracy, Completeness, and Helpfulness — useful when you're comparing 6 models and…
2024 · thisorthis.ai · its alternatives →
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