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AI · alternatives · 2026

24 alternatives to Snappy - LLMs Speed Test

Benchmark your LLMs in Seconds ⚡

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1

    Compare LLMs on your data, measure, and pick the best.

    Apr 2026 · trismik.com · its alternatives →

  2. 2

    Test-driven development for LLMs

    2023 · benchllm.com · its alternatives →

  3. 3
    LLM Stats▲293

    I 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 →

  4. 4

    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 →

  5. 5

    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.

    5d ago · llmspeed.dev · its alternatives →

  6. 6AT

    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 →

  7. 7

    Measure Your LLM's Speed, Right on Your Device!

    2025 · llmspeedcheck.com · its alternatives →

  8. 8
    Taylor AI▲118

    Fine-tune open source LLMs in minutes

    2023 · trytaylor.ai · its alternatives →

  9. 9

    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 →

  10. 10

    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 →

  11. 11

    LLM benchmarking tool for task-specific metrics on your data

    2023 · github.com · its alternatives →

  12. 12UD

    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 →

  13. 13

    Test LLM prompts & models side-by-side against many inputs

    2024 · its alternatives →

  14. 14TL
  15. 15

    An open source Next app template to monitor your AI apps

    2025 · github.com · its alternatives →

  16. 16

    Recently I've been working on making LLM evaluations fast by using bayesian optimization to select a sensible subset. Bayesian optimization is used because it’s good for exploration / exploitation of expensive black box (paraphrase, LLM). I would love to hear your thoughts and suggestions on this!

    2024 · github.com · its alternatives →

  17. 17

    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 →

  18. 18
    Pioneer▲113

    Fine-tune any LLM in minutes, with one prompt

    Apr 2026 · pioneer.ai · its alternatives →

  19. 19

    I have been working in AI space for a while now, first at FAANG with ML since 2021, then with LLM in start-ups since early 2023. I think LLM Application development is extremely iterative, more so than any other types of development. This is because to improve an LLM application performance (accuracy, hallucinations, latency, cost), you need to try various combinations of LLM models, prompt templates (e.g., few-shot, chain-of-thought), prompt context with different RAG architecture, different agent architecture, and more. There are thousands of possible combinations and you need a process…

    2024 · github.com · its alternatives →

  20. 20

    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 →

  21. 21WM

    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 →

  22. 22
    AnyLLM▲20

    10+ LLMs at 10x speed. Think we're kidding. Test it now!

    2025 · its alternatives →

  23. 23

    Track and improve your visibility on AI Search

    Dec 2025 · llmpulse.ai · its alternatives →

  24. 24
    Narev▲7

    Hey! I want to get your feedback on our A/B testing platform for LLMs. Giving a 100 day Pro trial to anyone who signs up this week. The premise: in 10 minutes compare a bunch of model/parameter/prompt combos to find the best point on the quality-latency-cost tradeoff. Enter your data manually or sync from your tracing platform. ~300 models to select from. Here is a 1 minute Loom: https://www.loom.com/share/39b7cd24166c4e1fafd5e7fbd12a9d4d?...

    2025 · narev.ai · 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 →