AI · alternatives · 2026
24 alternatives to Forge Agent
Swarm Agents That Turn Slow PyTorch Into Fast GPU Kernels
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 2 we have checked on their own sites, 2 of them free or with a free tier.
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Hi HN, I'm Antoine Zambelli, AI Director at Texas Instruments. I built Forge, an open-source reliability layer for self-hosted LLM tool-calling. What it does: - Adds domain-and-tool-agnostic guardrails (retry nudges, step enforcement, error recovery, VRAM-aware context management) to local models running on consumer hardware - Takes an 8B model from ~53% to ~99% on multi-step agentic workflows without changing the model - just the system around it - Ships with an eval harness and interactive dashboard so you can reproduce every number I wanted to run a handful of always-on agentic systems…
May 2026 · github.com · its alternatives →
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Hey HN, We just recently launched Forge – an AI model API platform that lets you access and call AI models from multiple providers in one place. Find it on our website: https://tensorblock.co/forge Some key features: Unified API Key – Store multiple provider API keys and access all with a single Forge API key. OpenAI API Compatible – Drop-in replacement for any application that uses OpenAI’s API. Advanced Security – Strong Encryption for API keys with JWT-based authentication. Client Management – Easy key and user management via included command-line interface. Open-source –…
2025 · tensorblock.co · its alternatives →
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The video demo runs a 7b Model on a normal gaming GPU. I think it already works quite well (accounting for the limited hardware power). :)
2024 · github.com · its alternatives →
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Bolt Forgefree tier, from $25/mo▲249Bolt's new agent with open-source models and 50X usage
Sep 2026 · bolt.new · its alternatives →
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Demo of agent based model on GPU with CUDA and OpenGL (Windows/Linux) Agent instances on GPU memory Uses SSBO for instanced objects (with GLSL 450 shaders) CUDA OpenGL interops Renders with GLFW3 window manager Dynamic camera views in OpenGL (pan,zoom with mouse) Libraries installed using vcpkg (https://github.com/KienTTran/ABMGPU)
2023 · github.com · its alternatives →
- 6Verdent Deck▲295
Hi HN! We just launched Verdent, an AI coding agent that actually plans before it codes, tests its own work, and delivers production-ready results without you having to clean up after it. tl;dr Check out the website [1] and read the story [2] - The problem: Current AI tools dump code and leave you to debug. You ask for "build a login endpoint" and get a passwordless JWT mess that doesn't fit your project. We've talked to hundreds of engineers who are frustrated with having to micromanage AI output. - What we built: Verdent works more like a senior engineer. It asks clarifying questions…
2025 · verdent.ai · its alternatives →
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A langgraph based workflow with a C++ CUDA suite to optimize CUDA kernels - bertaye/agentic-cuda-optimizer
26d ago · github.com · its alternatives →
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Get 10x speed for building automations. AI copilot is here
2025 · agentcraft.pro · its alternatives →
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RunInfra▲156Describe the AI model you need and get an optimized AI
Jul 2026 · runinfra.ai · its alternatives →
- 11RL
Hello Hacker News! We're Yangqing, Xiang and JJ from lepton.ai. We are building a platform to run any AI models as easy as writing local code, and to get your favorite models in minutes. It's like container for AI, but without the hassle of actually building a docker image. We built and contributed to some of the world's most popular AI software - PyTorch 1.0, ONNX, Caffe, etcd, Kubernetes, etc. We also managed hundreds of thousands of computers in our previous jobs. And we found that the AI software stack is usually unnecessarily complex - and we want to change that. Imagine if you are a…
2023 · lepton.ai · its alternatives →
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Hi HN, I’m Joe. My friends Matthew, Jake and I are building Luminal (https://luminalai.com/), a GPU compiler for automatically generating fast GPU kernels for AI models. It uses search-based compilation to achieve high performance. We take high level model code, like you'd have in PyTorch, and generate very fast GPU code. We do that without using LLMs or AI - rather, we pose it as a search problem. Our compiler builds a search space, generates millions of possible kernels, and then searches through it to minimize runtime. You can try out a demo in `demos/matmul` on mac to…
2025 · github.com · its alternatives →
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Minimal kernel to make any AI coding agent stateful. Clone, point your agent, go. - oguzbilgic/agent-kernel
Mar 2026 · github.com · its alternatives →
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Lightning▲83AI code editor for PyTorch development on GPU workspaces
Oct 2025 · lightning.ai · its alternatives →
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We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
2024 · github.com · its alternatives →
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com · its alternatives →
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We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
2025 · github.com · its alternatives →
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I'm an "ideas person" who messes around with AI on a low budget. I got tired of watching my tokens vanish and context windows filling up while agents fumbled around trying to find the right thing. Agents don't flail like they used to with shell tools, but there are still weak/blind spots and back-and-forth episodes — especially when using tools in combination/sequence. So I built "tilth" today. Or rather, AI built it — every line is Opus 4.6. I spent a lot of my precious tokens getting it to "not shit" (at least several of the different vendors' AI overlords assure me it's not…
Feb 2026 · github.com · its alternatives →
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Cursor published a great post last week on scaling long-running autonomous coding agents to build a browser. We’ve been exploring a similar idea, but applied to math proofs We show how a swarm of agents, coordinated via shared memory, can generate a Lean proof for a non-trivial multi-step math problem-Putnan A2-that a single agent struggled with. We were feeling fancy so we wrote a full post and captured the runtime. Harness will be public soon(tm) for you to run it yourself.
Mar 2026 · ensue.dev · its alternatives →
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I’ve been working on a temporal database for agents that combines graphs, tables, and compute. While building it, I ended up needing an agent framework that could handle both simple tool-use tasks and more graph-based execution, so I pulled that out into a separate project, Agent Forge. Agent Forge uses a two-tier execution model: * a heuristic router decides whether a request is simple or complex * simple requests go through a lightweight agent loop with a single system prompt and tool-calling loop * more complex requests can use memory retrieval, reflection constraints, tree search, and…
Mar 2026 · github.com · its alternatives →
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ADK-Rust▲6Hey everyone! I'm excited to share ADK-Rust - a production-ready implementation of Google's Agent Development Kit in Rust. Why Rust? After working extensively with adk-python in developing an ai agent factory at zavora.ai, I wanted to bring the same powerful agent development patterns to the Rust ecosystem, targeting use cases where: Performance is critical - Rust's zero-cost abstractions and memory safety Deployment size matters - Single binary with no runtime dependencies Systems-level integration - Embedded systems, edge computing, IoT Concurrency at scale - Rust's async/await with…
Dec 2025 · adk-rust.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →