---
title: GGUF Cloud - Deploy Any Open LLM as Your Own API | ModelsLab
description: Paste a HuggingFace GGUF link, pick a GPU, and get a dedicated OpenAI- and Anthropic-compatible LLM endpoint. Flat monthly price per dedicated GPU, no per-token charges, no DevOps.
url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/gguf-cloud
canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/gguf-cloud
type: website
component: Seo/GgufCloud
generated_at: 2026-06-30T06:52:38.407478Z
---
GGUF Cloud
Deploy any open LLM as your own API
---
Paste a HuggingFace GGUF link, pick a GPU, and get a dedicated OpenAI- and Anthropic-compatible endpoint. Flat monthly price. No DevOps.
[Deploy a model](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register) [API reference](https://modelslab-frontend-v2-927501783998.us-east4.run.app/gguf-cloud/api) [View pricing](#pricing)
Build your endpoint
Configure your deployment
---
Pick a trending model — or paste any HuggingFace GGUF link — then choose a GPU and deploy. We pre-select the cheapest card that fits and re-check it before you pay.
01### Pick a trending model
Top GGUF models on HuggingFace, updated daily.
AllChatCodingReasoning
Llama 3.1 8B Instruct 8B · Q4\_K\_M · 4.92GBQwen2.5 7B Instruct 7B · Q4\_K\_M · 4.68GBQwen2.5 Coder 32B 32B · Q4\_K\_M · 19.9GBMistral Nemo 12B 12B · Q4\_K\_M · 7.48GBMixtral 8x7B Instruct 47B · Q4\_K\_M · 26.4GBPhi-4 14B 14B · Q4\_K\_M · 9.05GBDeepSeek-R1-Distill-Qwen 32B 32B · Q4\_K\_M · 19.9GBLlama 3.3 70B Instruct 70B · Q4\_K\_M · 42.5GB
or
Paste any HuggingFace GGUF link
02### Pick a GPU
One flat monthly price — no per-token or idle charges.
RTX 3090 24GB · Standard $249 per monthRTX 4090 Fits 24GB · Fast $499 per monthRTX 5090 32GB · Fastest (consumer) $749 per monthRTX A6000 48GB · Big VRAM $899 per monthA100 80GB 80GB · Datacenter $1,499 per monthRTX 6000 PRO 96GB · Workstation (Blackwell) $1,999 per monthH100 80GB 80GB · Datacenter (max) $2,499 per month
You're deploying
Llama 3.1 8B Instruct on RTX 4090 · $499/mo
[Bring your own GGUF](https://modelslab-frontend-v2-927501783998.us-east4.run.app/dashboard/gguf/new) [Deploy Llama 3.1 8B Instruct on RTX 4090](https://modelslab-frontend-v2-927501783998.us-east4.run.app/dashboard/gguf/new?gpu_type=rtx4090)
From link to live endpoint in three steps
---
No Dockerfiles, no vLLM configs, no GPU shopping. Paste, pick, deploy.
01
### Paste a GGUF link
Drop in a HuggingFace GGUF repo or a direct .gguf URL — or pick one of the trending models. Choose your quant: Q4\_K\_M, Q5\_K\_M or Q8\_0.
02
### We recommend a GPU
GGUF Cloud reads the model size and pre-selects the cheapest dedicated GPU that fits, showing the flat monthly price before you commit.
03
### Get your endpoint + key
One click spins up a dedicated llama.cpp container. You get an OpenAI- and Anthropic-compatible endpoint and your ModelsLab API key.
[Deploy a model](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register)
Why GGUF Cloud
Built for the models everyone else turns away
---
### GGUF & llama.cpp native
Bring your own quantization — Q4, Q6 or Q8. The managed LLM hosts force vLLM and safetensors and reject GGUF outright. We run it as a first-class primitive.
### Flat monthly per GPU
One predictable price per dedicated GPU. No per-token billing, no idle meter ticking at zero requests — the single most-complained-about thing in the category.
### Dedicated single-tenant
Your model runs on its own GPU. No noisy neighbours, no shared-pool throttling, no preemptible boxes vanishing mid-run. Guaranteed throughput.
### OpenAI and Anthropic
Every endpoint speaks both protocols natively. Point the OpenAI SDK, the Anthropic SDK, or Claude Code straight at your own model — no translation layer.
### Automatic GPU sizing
We compute the VRAM your model needs from its parameters, quant and context, then recommend the cheapest card that fits. Nobody else does this.
### Transparent pricing
Every GPU tier and its monthly price is on this page. No "contact sales" wall to find out what a dedicated endpoint actually costs.
Point any SDK at your own model
---
Your endpoint speaks both the OpenAI and Anthropic protocols natively — no shim, no rewrites. Swap the base URL and keep your existing code.
### OpenAI SDK (Python)
Python
```
1from openai import OpenAI
2
3client = OpenAI(
4 base_url="https://modelslab.com/api/gguf/{id}/v1",
5 api_key="$MODELSLAB_API_KEY",
6)
7
8resp = client.chat.completions.create(
9 model="local",
10 messages=[{"role": "user", "content": "Explain GGUF in one line."}],
11 stream=True,
12)
13for chunk in resp:
14 print(chunk.choices[0].delta.content or "", end="")
```
### Anthropic SDK (Python)
Python
```
1from anthropic import Anthropic
2
3# Point Claude Code or the Anthropic SDK at your own model.
4client = Anthropic(
5 base_url="https://modelslab.com/api/gguf/{id}",
6 api_key="$MODELSLAB_API_KEY",
7)
8
9msg = client.messages.create(
10 model="local",
11 max_tokens=512,
12 messages=[{"role": "user", "content": "Explain GGUF in one line."}],
13)
14print(msg.content[0].text)
```
### cURL
bash
```
1curl https://modelslab.com/api/gguf/{id}/v1/chat/completions \
2 -H "Authorization: Bearer $MODELSLAB_API_KEY" \
3 -H "Content-Type: application/json" \
4 -d '{
5 "model": "local",
6 "messages": [{"role": "user", "content": "Hello!"}]
7 }'
```
[Read the full API docs](https://modelslab-frontend-v2-927501783998.us-east4.run.app/gguf-cloud/api)
Deploy a trending model
---
Llama, Qwen, Mistral, Mixtral, Phi, DeepSeek and more — pre-verified GGUF builds, or paste any HuggingFace repo of your own.
### Llama 3.1 8B Instruct
8B · Q4\_K\_M · 4.92 GB
chat popular
Fits RTX 4090 · $499/mo
### Qwen2.5 7B Instruct
7B · Q4\_K\_M · 4.68 GB
chat
Fits RTX 4090 · $499/mo
### Qwen2.5 Coder 32B
32B · Q4\_K\_M · 19.9 GB
code
Fits RTX A6000 · $899/mo
### Mistral Nemo 12B
12B · Q4\_K\_M · 7.48 GB
chat
Fits RTX 4090 · $499/mo
### Mixtral 8x7B Instruct
47B · Q4\_K\_M · 26.4 GB
chat moe
Fits RTX A6000 · $899/mo
### Phi-4 14B
14B · Q4\_K\_M · 9.05 GB
reasoning
Fits RTX 4090 · $499/mo
### DeepSeek-R1-Distill-Qwen 32B
32B · Q4\_K\_M · 19.9 GB
reasoning
Fits RTX A6000 · $899/mo
### Llama 3.3 70B Instruct
70B · Q4\_K\_M · 42.5 GB
chat frontier
Fits A100 80GB · $1,499/mo
One flat price per dedicated GPU
---
Pick the card your model fits on. Billed monthly, cancel anytime — no per-token charges, no idle meter, no surprises.
### RTX 3090
Entry
Standard
$249 /mo
VRAM24 GB
Usable for weights~21 GB
[Deploy on RTX 3090](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register)
### RTX 4090
Fast
$499 /mo
VRAM24 GB
Usable for weights~21 GB
[Deploy on RTX 4090](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register)
### RTX 5090
Fastest (consumer)
$749 /mo
VRAM32 GB
Usable for weights~28 GB
[Deploy on RTX 5090](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register)
### RTX A6000
Big VRAM
$899 /mo
VRAM48 GB
Usable for weights~43 GB
[Deploy on RTX A6000](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register)
### A100 80GB
Datacenter
$1,499 /mo
VRAM80 GB
Usable for weights~72 GB
[Deploy on A100 80GB](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register)
### RTX 6000 PRO
Workstation (Blackwell)
$1,999 /mo
VRAM96 GB
Usable for weights~86 GB
[Deploy on RTX 6000 PRO](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register)
### H100 80GB
Datacenter (max)
$2,499 /mo
VRAM80 GB
Usable for weights~72 GB
[Deploy on H100 80GB](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register)
- Flat monthly billing
- Cancel anytime
- No per-token charges
- Pause to stop compute billing
Why teams pick GGUF Cloud
---
The managed LLM hosts reject GGUF. The dedicated GPU hosts bill hourly and punish idle time. GGUF Cloud is the synthesis.
| Capability | GGUF Cloud | HF Endpoints | Together / Fireworks | Featherless |
|---|---|---|---|---|
| Runs GGUF / llama.cpp | Yes | Yes | Rejects GGUF | FP8 only |
| Bring your own quant | Q4 / Q6 / Q8 | Limited | No | No |
| Dedicated single-tenant | Yes | Yes | Shared | Shared |
| Flat monthly price | Per GPU | Hourly | Per token | Yes |
| No idle / per-token charges | Yes | Idle billed | Per token | Yes |
| OpenAI + Anthropic API | Both | OpenAI only | Varies | OpenAI only |
| Automatic GPU recommendation | Yes | No | No | No |
Comparison reflects each provider's standard offering as of June 2026. Based on publicly documented pricing and engine support.
GGUF Cloud FAQ
---
### What is GGUF Cloud?
GGUF Cloud is a managed hosting product that turns any open large language model into your own dedicated API. You paste a HuggingFace GGUF link or pick a trending model, GGUF Cloud recommends a GPU that fits, and one click spins up a dedicated llama.cpp (llama-server) container. You get an OpenAI- and Anthropic-compatible endpoint plus your API key, for a flat monthly price per GPU.
### How do I deploy a GGUF model as an API?
Sign up for ModelsLab, open GGUF Cloud, and either paste a HuggingFace GGUF repo (for example bartowski/Meta-Llama-3.1-8B-Instruct-GGUF) or select a trending model. Choose a quantization, accept the recommended GPU, and subscribe. Within a few minutes you receive a dedicated endpoint at https://modelslab.com/api/gguf/{id} that you authenticate with your ModelsLab API key.
### Is the endpoint OpenAI and Anthropic compatible?
Yes. Every GGUF Cloud endpoint exposes both the OpenAI API (/v1/chat/completions, /v1/completions, /v1/embeddings, /v1/models) and the Anthropic Messages API (/v1/messages) natively through llama-server. Point the OpenAI SDK at .../api/gguf/{id}/v1, point the Anthropic SDK or Claude Code at .../api/gguf/{id}, and use your ModelsLab API key as the key.
### How much does it cost to host an LLM on GGUF Cloud?
You pay one flat monthly price per dedicated GPU — there are no per-token charges and no idle meter. Tiers run from an RTX 3090 (24 GB) for smaller models up to an H100 (80 GB) for 70B-class models. The exact monthly price for every GPU is listed on the pricing section of this page.
### Which models and GPUs can I use?
Any GGUF model that fits in a single GPU works — Llama, Qwen, Mistral, Mixtral, Gemma, Phi, DeepSeek distills and more, in Q4\_K\_M, Q5\_K\_M or Q8\_0. GGUF Cloud reads the model size and recommends the cheapest GPU that fits, from RTX 3090 / 4090 / 5090 and RTX A6000 up to A100 and H100 80 GB.
### Why dedicated instead of a shared LLM pool?
Shared pools throttle under load, cap quality at FP8, and can drop requests mid-run. A dedicated single-tenant GPU gives you guaranteed throughput, your choice of GGUF quant, and no noisy neighbours — which matters for agents, coding assistants, roleplay and any latency-sensitive workload.
### Can I pause or swap a deployment?
Yes. You can pause an endpoint to stop compute billing while keeping the weights saved (it resumes warm in a minute or two), swap to a different GGUF or quant on the same GPU, resize the GPU tier, or delete the deployment and cancel the subscription at any time.
Deploy your first model in minutes
---
Bring your own GGUF or pick a trending one. Get a dedicated, single-tenant endpoint that speaks OpenAI and Anthropic — for a price you can predict.
[Deploy a model](https://modelslab-frontend-v2-927501783998.us-east4.run.app/register) [See GPU pricing](#pricing)
Explore Our Other Solutions
---
Unlock your creative potential and scale your business with ModelsLab's comprehensive suite of AI-powered solutions.
[Imagen
### AI Image Generation & Tools
Generate, edit, upscale, and transform images with state-of-the-art AI models.
Explore Imagen](https://modelslab-frontend-v2-927501783998.us-east4.run.app/imagen) [Audio Gen
### AI Audio Generation
Text-to-speech, voice cloning, music generation, and audio processing APIs.
Explore Audio Gen](https://modelslab-frontend-v2-927501783998.us-east4.run.app/audio-gen) [Video Fusion
### AI Video Generation & Tools
Create, edit, and enhance videos with AI-powered generation and transformation tools.
Explore Video Fusion](https://modelslab-frontend-v2-927501783998.us-east4.run.app/video-generation) [3D Verse
### Create Stunning 3D Models
Transform images and text into 3D models with advanced AI-powered generation.
Explore 3D Verse](https://modelslab-frontend-v2-927501783998.us-east4.run.app/text-to-3d)
---
*This markdown version is optimized for AI agents and LLMs.*
**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)
---
*Generated by ModelsLab - 2026-06-30*