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Llmspeed is a website that lets visitors compare local language-model speed estimates across a range of hardware and models. Its figures mix community benchmark measurements with estimates derived from similar systems or hardware specifications, so results are indicative rather than guaranteed.
Llmspeed has published a browser for comparing how quickly different language models may run on local hardware, giving prospective buyers a way to inspect performance estimates before choosing a device. The site says its results combine community benchmark measurements with figures estimated from similar setups or projected from specifications, so not every entry is a direct test.
Visitors can browse by hardware or by model. The listed systems span desktop graphics cards, AMD accelerators, Apple computers, laptops, CPU-only configurations and cloud GPUs. The model list includes several families and sizes, from smaller models such as Llama 3.1 8B to larger entries such as GPT-OSS 120B.
Llmspeed describes its figures as estimates for a short prompt on a single device. It says measured numbers come from community sources including r/LocalLLaMA and localscore.ai, while other results are derived from similar setups or projected from hardware specifications. The site links to an open-source project on GitHub.
That distinction matters when reading comparisons: a number based on a community benchmark is not the same as a result Llmspeed measured under a single standardized test. The source material does not provide a complete methodology, per-entry provenance, or a detailed explanation of how estimates are calculated.
A Preview Before Hardware Shopping
Running a model locally can depend on both the model’s size and the available hardware. A comparison tool can help shoppers narrow their options before spending on a graphics card, computer or accelerator, especially when they are weighing different device types or considering whether a model fits their setup.
But Llmspeed is best treated as a planning aid, not a promise of real-world speed. Results can vary with software, model settings, prompt length, memory limits and other parts of a particular setup. Because the site combines measured and projected figures, users need to check what kind of figure they are viewing before drawing conclusions about a purchase.
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Models and Devices in the Catalog
The hardware browser ranges from consumer GPUs such as the RTX 3060 and RTX 5090 to higher-memory workstation and data-center options, Apple systems, AMD products, and cloud GPUs including the H100 and H200. It also includes a CPU-only Ryzen 9 9950X configuration, indicating that the catalog is not limited to dedicated graphics hardware.
The model browser covers a range of listed sizes and variants, including Qwen, Gemma, DeepSeek, GLM, GPT-OSS and Llama entries. These lists show the breadth of the comparison tool, but the supplied source does not establish that every hardware-and-model combination has been directly tested or is available to run on each system.
“Estimates for a short prompt on a single device.”
— Llmspeed website
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How Comparable Are the Estimates?
The source does not state how many results are direct measurements, when individual benchmarks were collected, or whether different submissions use the same software and settings. It also does not explain the calculation method behind each projected figure. As a result, readers cannot determine from the supplied material alone how closely a particular estimate will match their own machine.
It is also unclear whether the catalog is complete or how often its entries are updated. The site’s short-prompt, single-device framing does not establish performance for longer prompts, sustained use, multi-device setups or other workloads.
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Check Results Against Your Setup
People considering a purchase can use Llmspeed to compare listed hardware and models, then check the linked project and underlying community benchmark sources for details where available. The source material does not announce a schedule for updates or a specific next release.
For a buying decision, the next useful step is to confirm whether the relevant result is measured or projected and compare it with a workload that matches the intended use. Until the site supplies more detail about testing conditions and estimate methods, its figures should be read as guidance rather than a guarantee.
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Key Questions
What is Llmspeed?
Llmspeed is a website for browsing local language-model speed figures by hardware or model.
Are all its speed figures direct benchmark results?
No. The site says some figures come from community benchmarks, while others are derived from similar systems or projected from hardware specifications.
What kind of workload do the estimates cover?
Llmspeed labels them as estimates for a short prompt on a single device. The supplied source does not specify how they apply to other workloads.
Which hardware does the site list?
The catalog includes consumer and workstation GPUs, AMD accelerators, Apple computers, laptops, a CPU-only system and cloud GPUs.
Can the figures guarantee performance on a machine I buy?
No guarantee is stated. Results may differ by software, settings, workload and hardware configuration, and the site mixes measured data with estimates.
Source: hn
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