Llama & open models
Open Models Without the GPU Bill.
Meta's Llama family is why a self-hosted assistant stopped being a lab-only idea. But there are two honest routes to an open model: run the weights yourself, or open @vustbot and chat with DeepSeek, Qwen, GLM, Kimi, MiniMax and LongCat — no GPU, no API key, no separate account.
See the difference
Self-host or hosted chat — what each route actually costs you.
Who reads this page
- Open-weight fans
- Want open-model answers without buying a GPU
- Chat with DeepSeek, Qwen, GLM, Kimi, MiniMax and LongCat inside @vustbot.
- Privacy-minded builders
- Weighing a local stack against a hosted chat
- A straight read on what running weights yourself actually buys and costs.
- Model explorers
- Want to compare answers side by side
- Put the same task to two models in one thread and read both replies.
Two honest routes to an open model
- 01
Run the weights yourself
Download the open weights, install a runner such as Ollama or LM Studio, and you own the stack end to end — hardware, updates, privacy and all.
- 02
Or skip the setup
Open @vustbot and ask. Nothing to install, no API key to mint, no separate account.
- 03
Switch models mid-conversation
@vustbot runs open models next to the frontier ones — GPT, Claude, Gemini and Grok are in the same thread, one tap away.
Try an open model in one chat
Open @vustbot and switch between DeepSeek, Qwen, GLM, Kimi, MiniMax and LongCat in the same thread — no GPU, no API key, no separate account.
What to know before you choose
What Llama is
Meta's open-weight model family, whose recent releases carry multimodal input and very long context. It is the reference point for open, privacy-preserving stacks, and its licence is what made a self-hosted assistant realistic for ordinary teams. Check Meta's own site for the current releases and licence terms.
Where open weights genuinely win
You can audit them, fine-tune them, run them offline and keep every token on your own hardware. That is the right call for regulated data, air-gapped work and anything that has to answer identically a year from now.
Where a hosted chat wins
No GPU to buy, no runner to keep updated, no quantisation trade-offs to reason about. @vustbot serves the open-weight families DeepSeek, Qwen, GLM, Kimi, MiniMax and LongCat — DeepSeek answers on the free tier, and the larger open models are on the Pro plan. The exact price and the payment options are shown inside Telegram.
Frequently asked questions
Which open models can I chat with in @vustbot?
@vustbot carries the open-weight families DeepSeek, Qwen, GLM, Kimi, MiniMax and LongCat, next to the frontier models. You switch between them inside one conversation, so a single question can go to two different models without starting over.
What is Llama?
Llama is Meta's open-weight model family, whose recent releases carry multimodal input and very long context. Its permissive licence is a large part of why a self-hosted assistant became realistic for ordinary teams rather than just labs.
Is it worth running open weights on my own machine?
Yes when you need auditability, offline operation, fine-tuning, or a hard guarantee that nothing leaves your hardware — regulated data and air-gapped work are the clear cases. Rarely when you simply want good answers: consumer hardware pushes you toward smaller quantised models, and you inherit the drivers, updates and disk space permanently.
Do I need an API key or a developer account?
No. @vustbot lives inside Telegram — you open the chat and ask. There is no key to mint, no console to configure and no second account to maintain.
What does it cost?
DeepSeek answers on the free tier, and the larger open models are on the Pro plan.
Ready when you are
Open models, without the GPU bill.
Self-hosting buys you control and costs you setup. @vustbot gives you DeepSeek, Qwen, GLM, Kimi, MiniMax and LongCat in a Telegram chat instead — switchable mid-conversation, next to the frontier models.