AI · alternatives · 2026
24 alternatives to Llmspeed – feel how fast a local LLM runs before you buy the hardware
Pick hardware and a model, and feel the real speed of a local LLM before you buy. Simulates tokens/sec and time-to-first-token from verified benchmarks for GPUs, Macs, and more.
Llmspeed lets users simulate the performance of local language models on different hardware before purchasing. Users select a GPU, Mac, or other device along with a model to see estimated tokens per second and… 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 1 we have checked on their own sites, 1 of them free or with a free tier.
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Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. - Andyyyy64/whichllm
May 2026 · github.com · its alternatives →
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LLM Stats▲293I was overspending on GPT-4o. It was really hard to compare different models I could switch to, so I built this LLM comparison tool. It shows leaderboards, pricing, and performance data across 100+ LLMs (including all major providers and open-source models). Key features: - Live pricing comparisons - Benchmark Scores (MMLU, HumanEval, GPQA, etc.) - Context length vs cost analysis - Speed/throughput tests across providers - Quality vs price visualizations - Open source (all data verifiable) Try it out: https://llmstats.com I'd like to know your opinion :) Tech stack: Next.js,…
Oct 2025 · llm-stats.com · its alternatives →
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A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me. But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility. I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context.…
Jul 2026 · github.com · its alternatives →
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Hey Folks! I've been building an open source benchmark for measuring local LLM performance on your own hardware. The benchmarking tool is a CLI written on top of Llamafile to allow for portability across different hardware setups and operating systems. The website is a database of results from the benchmark, allowing you to explore the performance of different models and hardware configurations. Please give it a try! Any feedback and contribution is much appreciated. I'd love for this to serve as a helpful resource for the local AI community. For more check out: - Website:…
2025 · localscore.ai · 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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Measure Your LLM's Speed, Right on Your Device!
2025 · llmspeedcheck.com · its alternatives →
- 7WM
Pick a Mac and a model, get the memory it needs and the tokens/sec to expect. Covers M1 to M6, every unified memory size, Q4 to FP16. Formula fitted and validated on our own measurements on two machines.
4d ago · macyou.co · its alternatives →
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Here's a project I've been working on for the last few months. It's a new (I think) algorithm, that allows to adjust smoothly - and in real time - how many calculations you'd like to do during inference of an LLM model. It seems that it's possible to do just 20-25% of weight multiplications instead of all of them, and still get good inference results. I implemented it to run on M1/M2/M3 GPU. The mmul approximation itself can be pushed to run 2x fast before the quality of output collapses. The inference speed is just a bit faster than Llama.cpp's, because the rest of implementation…
2024 · asciinema.org · its alternatives →
- 9AT
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
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LLM Pricing▲178LLMs price comparison tool developed and updated by LLM
2024 · ailesson.io · its alternatives →
- 11CI
One of the most frequent questions one faces while running LLMs locally is: I have xx RAM and yy GPU, Can I run zz LLM model ? I have vibe coded a simple application to help you with just that. Update: A lot of great feedback for me to improve the app. Thank you all.
2025 · can-i-run-this-llm-blue.vercel.app · its alternatives →
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The LLM providers are constantly adding new models and updating their API prices. Anyone building AI applications knows that these prices are very important to their bottom line. The only place I am aware of is going to these provider's individual website pages to check the price per token. To solve this inconvenience I spent a few hours making pricepertoken.com which has the latest model's up-to-date prices all in one place. Thinking about adding image models too especially since you have multiple options (fal, replicate) to use the same model and the prices are not always the same.
2025 · pricepertoken.com · its alternatives →
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Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization - RahulSChand/gpu_poor
2023 · github.com · its alternatives →
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Built a simple web app that tells you which open-source LLMs will work on your hardware. It auto-detects your specs, shows compatible models from Hugging Face, gives realistic performance estimates (tokens/sec), and recommends quantization settings. You can also manually input specs to see "what if I upgraded my RAM?" Made this after wasting time downloading giant models only to find they crawled on my hardware. Hope it saves you some frustration!
2025 · caniusellm.com · its alternatives →
- 15RY
Hey HN, we've just finished building a dynamic router for LLMs, which takes each prompt and sends it to the most appropriate model and provider. We'd love to know what you think! Here is a quick(ish) screen-recroding explaining how it works: https://youtu.be/ZpY6SIkBosE Best results when training a custom router on your own prompt data: https://youtu.be/9JYqNbIEac0 The router balances user preferences for quality, speed and cost. The end result is higher quality and faster LLM responses at lower cost. The quality for each candidate LLM is predicted ahead of time…
2024 · unify.ai · its alternatives →
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- 17UD
Hey HN! I’m the founder of Unify, and we’ve just released our Model Hub, which provides a collection of LLM endpoints with live runtime benchmarks all plotted across time: https://unify.ai/hub A key finding is that static tabular runtime benchmarks for LLMs simply do not work. It’s necessary to take a time-series perspective, and plot the variations through time. We currently have 21 models provided by: Anyscale, Perplexity AI, Replicate, Together AI, OctoAI, Mistral AI and OpenAI, with more on the roadmap. We test across different regions (Asia, US, Europe), with varied…
2024 · its alternatives →
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Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. - MakazhanAlpamys/Soup
Aug 2026 · github.com · its alternatives →
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Pick a Mac mini, Mac Studio, DGX Spark or Strix Halo box, see which open models fit and how fast they run, and how much usage it takes to break even against paying an API. It is willing to say: it doesn
Sep 2026 · sunkcost.ai · its alternatives →
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A fast.com style benchmarking tool for LLM APIs. Compare OpenAI, Anthropic, Groq, Cerebras, Fireworks AI, Mistral, OpenRouter, Google Gemini, x.ai, z.ai, Kimi, and local models. See live streaming output with real-time throughput metrics. Race Mode lets you run multiple providers in parallel and wat
Jun 2026 · iamspeed.dev · its alternatives →
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Hi everyone, I just released an open source load testing tool for LLMs: https://github.com/twerkmeister/tokenflood === What is it and what problems does it solve? === Tokenflood is a load testing tool for instruction-tuned LLMs hat can simulate arbitrary LLM loads in terms of prompt, prefix, and output lengths and requests per second. Instead of first collecting prompt data for different load types, you can configure the desired parameters for your load test and you are good to go. It also let's you assess the latency effects of potential prompt parameter changes before…
Nov 2025 · github.com · its alternatives →
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LLM·RAG·VLM·아바타 워크로드를 GPU·CPU·RAM·스토리지·네트워크 구성과 경제형·권장형·확장형 견적 3안으로 변환하는 오픈소스 AI 인프라 산정 도구
Aug 2026 · jaeseok614.github.io · its alternatives →
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If I have this hardware, Can I run that LLM model ?
2025 · can-i-run-this-llm-blue.vercel.app · its alternatives →
- 24
Free tool to check if your GPU can run local LLMs.
Jul 2026 · llmconfigurator.com · its alternatives →
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