AI · alternatives · 2026
24 alternatives to Banana.dev Serverless GPUs for Machine Learning Inference
Inference hosting for AI teams who ship fast and scale faster.
Banana.dev provides serverless GPU infrastructure designed for machine learning inference workloads. The platform allows developers to deploy and run machine learning models on GPUs without managing underlying… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Banana.dev Serverless GPUs for Machine Learning Inference launched in 2022; newer entries below may have overtaken it.
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Cerebrium▲300If you haven’t noticed, GPUs are scarce right now. The global boom in inference has demand growing faster than supply can keep up, and at Cerebrium ...
2024 · cerebrium.ai · its alternatives →
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General Compute▲315AI models that run on an inference cloud optimized for speed
May 2026 · generalcompute.com · its alternatives →
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- 6GA
2021 · inferrd.com · its alternatives →
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An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
2016 · github.com · its alternatives →
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Nano Banana 2▲416Hi HN — I’m an indie developer. I built Nano Banana 2 Playground, a simple web demo for generating images from text and transforming existing images (image-to-image). My goal was a fast, minimal UI that lets you iterate on prompts quickly and compare results without extra friction. I’d love feedback on: Prompt UX (what feels missing/confusing) Which controls/presets are actually useful How to communicate limitations and expected results clearly Thanks for taking a look — happy to answer questions and improve it based on your suggestions.
Feb 2026 · blog.google · its alternatives →
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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 →
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Deploying vision models is time consuming and tedious. Setting up dependencies. Fixing conflicts. Configuring TRT acceleration. Flashing (and re-flashing) NVIDIA Jetsons. A streamlined, developer-friendly solution for inference is needed. We, the Roboflow team, have been hard at work open sourcing Inference, an open source vision deployment solution. Our solution is designed with developers in mind, offering a HTTP-based interface. Run models on your hardware without having to write architecture-specific inference code. Here's a demo showing how to go from a model to GPU inference on a video…
2023 · github.com · its alternatives →
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Build your own high performance LLM inference engine in C++ and CUDA - a smaller version of vLLM - jmaczan/tiny-vllm
May 2026 · github.com · its alternatives →
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We wanted to do something very challenging to prove to ourselves that we can do anything we put our mind to. The reasoning for why we chose to build a toy TPU specifically is fairly simple: - Building a chip for ML workloads seemed cool - There was no well-documented open source repo for an ML accelerator that performed both inference and training None of us have real professional experience in hardware design, which, in a way, made the TPU even more appealing since we weren't able to estimate exactly how difficult it would be. As we worked on the initial stages of this project, we…
2025 · tinytpu.com · its alternatives →
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Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…
2022 · tensordock.com · its alternatives →
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GPU Functions: Deploy AI Models & Run Serverless Inference
2024 · buildfunctions.com · its alternatives →
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Tom from Tensil here - happy to answer questions! We developed Tensil to bring custom ML accelerators to people who don't have the resources of companies like Google, Facebook and Tesla. Currently, we're focused on supporting convolutional neural network inference on edge FPGA (field programmable gate array) platforms, but we aim to support all model architectures on a wide variety of fabrics for both training and inference. Tensil is different from other ML accelerators in that it is open source and really easy to use. For example, you can generate a custom accelerator with one command: $…
2022 · tensil.ai · its alternatives →
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I wanted to build an inference provider for proprietary AI models, but I did not have a huge GPU farm. I started experimenting with Serverless AI inference, but found out that coldstarts were huge. I went deep into the research and put together an engine that loads large models from SSD to VRAM up to ten times faster than alternatives. It works with vLLM, and transformers, and more coming soon. With this project you can hot-swap entire large models (32B) on demand. Its great for: Serverless AI Inference Robotics On Prem deployments Local Agents And Its open source. Let me know if anyone…
Nov 2025 · github.com · its alternatives →
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Hi HN, I'm Paul from Tensordyne. We build AI inference systems and chips on logarithmic math. We've put together an interactive Token Economics Calculator to help make apples-to-apples comparisons of inference hardware across vendors: We're interested in how closely it lines up with the community's view of the market. Why we built this Investors and customers kept asking how our system compares to others (NVIDIA and a growing list of startups). Plenty of publicly available data exists, but it's scattered and inconsistent. News articles, provider sites, Artificial Analysis, MLCommons, and now…
Nov 2025 · tensordyne.ai · its alternatives →
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2019 · isthisbananaripe.ml · its alternatives →
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Private inference app that lets you see the token entropy, explore and change the token probabilities. Just released on macOS, iOS version next then other platforms. Here's a demo of it in action running DeepSeek Terminus: https://youtu.be/kts098EL2PQ Would love to hear any feedback or feature requests from the community.
2025 · inferencer.com · its alternatives →
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Hey HN! Bob here, Founder and CEO of Salad (www.salad.com), a distributed cloud for AI inference at scale. *Why Salad?* Because there’s 400 Million consumer GPUs in the world (~100 Million AI-enabled RTX GPUS) and most of them lie unused for 18-22 hrs a day. These consumer GPUs offer similar or better cost-performance than high-end AI GPUs for many AI/ML use cases (Speech-to-text, batch jobs, text-to-image, computer vision to name a few). With Salad, we have activated this latent compute in everyday PCs to power AI/ML workloads. *How big is our network?* More than 1,900,000…
2024 · its alternatives →
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Nano Banana AI ▲10I built Nano Banana AI , a fast tool to edit existing images with text prompts. I made it because current tools felt slow and mostly focus on generating new images. This one is different: Image-to-image only — edit instead of generate. Fast — optimized inference on Gemini 2.5 Flash. Would love feedback on use cases or improvements.
2025 · geminiflashimage.art · its alternatives →
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Inference infrastructure for AI-native teams. Run, monitor, and optimize production AI workloads with lower cost, faster latency, and dedicated support from Inference.net.
2024 · inference.net · 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 →