LLMconfigurator.com
Free tool to check if your GPU can run local LLMs.
LLMconfigurator.com launched on July 16, 2026 with 7 votes, #2,664 of 24,623 launches that month and more than 90% of that year's launches.
What it does
Free GPU compatibility checker for local LLMs. Find which models (Llama 4, Gemma 4, DeepSeek V4, Qwen 3.5) your GPU can run. Calculate VRAM usage, compare cloud vs local costs, browse 75+ models, and get setup guides for Ollama, LM Studio, and phones.
Free tool to check if your GPU can run local LLMs. Compare 79 model families (167 variants) (Llama 4, DeepSeek R1, Qwen 3), calculate costs, read setup guides. Zero cloud dependency.
Check if your GPU can run local LLMs. Compare 79 model families (167 variants), calculate costs, and read setup guides. Zero cloudfrom llmconfigurator.com
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Can your GPU run this LLM?2023 · github.com · ▲15Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization - RahulSChand/gpu_poor
Find the best local LLM for your hardware, ranked by benchmarksMay 2026 · github.com · ▲283Find 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
Llama 3.1 70B on a single RTX 3090 via NVMe-to-GPU bypassing the CPUFeb 2026 · github.com · ▲395Hi everyone, I'm kinda involved in some retrogaming and with some experiments I ran into the following question: "It would be possible to run transformer models bypassing the cpu/ram, connecting the gpu to the nvme?" This is the result of that question itself and some weekend vibecoding (it has the linked library repository in the readme as well), it seems to work, even on consumer gpus, it should work better on professional ones tho
Llmspeed – feel how fast a local LLM runs before you buy the hardware5d ago · llmspeed.dev · ▲329Pick 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.
- CICan I run this LLM? (locally)2025 · can-i-run-this-llm-blue.vercel.app · ▲42
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.
Tune LLaMa3.1 on Google Cloud TPUs2024 · github.com · ▲189Hey HN, we wanted to share our repo where we fine-tuned Llama 3.1 on Google TPUs. We’re building AI infra to fine-tune and serve LLMs on non-NVIDIA GPUs (TPUs, Trainium, AMD GPUs). The problem: Right now, 90% of LLM workloads run on NVIDIA GPUs, but there are equally powerful and more cost-effective alternatives out there. For example, training and serving Llama 3.1 on Google TPUs is about 30% cheaper than NVIDIA GPUs. But developer tooling for non-NVIDIA chipsets is lacking. We felt this pain ourselves. We initially tried using PyTorch XLA to train Llama 3.1 on TPUs, but it was rough: xla…
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