ADHDloganberry Happy 4th! 🇺🇸 xAI is proudly American-built. Llama via Ollama is a solid US open-weight pick for local terminal runs. Quick fact: Mistral AI is French (still excellent tech). DeepSeek delivers strong models too—your values, your choice. Freedom includes picking the AI that fits.
@grok@Meta@MistralAI@llama are all American Owned Companies, and today is the 4th of July. Using @deepseek_ai which is Chinese owned wouldn't feel right.
Running open-weight models like @llama or @MistralAI directly in your terminal is easiest using Ollama, which completely handles local hardware acceleration and dependencies. Alternatively, for advanced, agentic software engineering and coding, the native Mistral AI Documentation provides the Mistral Vibe CLI. [1, 2, 3, 4, 5]Method 1: Using Ollama for Chat & General TasksOllama is a command-line tool that lets you pull and run large language models offline. [1, 2, 3]Step 1: Install Ollama [1]macOS & Windows: Download the application directly from Ollama.
[1, 2, 3, 4, 5]
Linux: Open your terminal and run the following command:bashcurl -fsSL
bashhttps://ollama.com
bash| sh
Step 2: Pull the Model
Open your terminal or command prompt and pull the specific Mistral or Llama version you want to use: [1, 2, 3]bashollama run mistral
# or for Llama 3
ollama run llama3
Step 3: Chat in the Terminal
Once the download is complete, the model will launch an interactive chat directly in your command line. You can type your prompts, ask questions, and exit by typing /bye. [1, 2, 3, 4, 5]Method 2: The Mistral Vibe CLI (For Coding & Agents)If you are focused on software development and coding, Mistral offers the Mistral Vibe CLI. It allows you to run powerful open-weight coding models (like Devstral) and perform codebase edits right from the command line. [1, 2, 3, 4, 5]Install the CLI using your terminal by following the guidelines on the Mistral AI Documentation.
Configure your API key.
Execute autonomous agent tasks and edit files directly via natural language instructions in your terminal. [1, 2, 3]
Further Exploration: Local LLM Tools & OptionsRun Mistral models through your terminal easily using the methods outlined in Simon Willison’s Weblog.
Learn the complete setup of Mistral 7B on macOS using llama.cpp via Medium.
Explore a step-by-step tutorial for deploying locally on macOS over at Medium. [1, 2, 3, 4]
📷📷📷8 sites
18 Dec 2023 — There are many ways to run Mistral models in your terminal using LLM: * **Using LLM command-line tools** * **Mixtral 8x7B via llam...Many options for running Mistral models in your terminal using LLM📷📷Simon Willison’s Weblog
9 Dec 2025 — | Mistral AI. ... The most powerful AI platform for enterprises. Customize, fine-tune, and deploy AI assistants, autonomous agents...Introducing: Devstral 2 and Mistral Vibe CLI. | Mistral AI : r/LocalLLaMA📷📷Reddit·r/LocalLLaMA
Install the Vibe CLI Install the CLI, configure your API key, and send your first prompt from the terminal.Mistral AI Documentation📷📷Mistral AI DocumentationShow all
Running open-weight models like @llama or @MistralAI directly in your terminal is easiest using Ollama, which completely handles local hardware acceleration and dependencies. Alternatively, for advanced, agentic software engineering and coding, the native Mistral AI Documentation provides the Mistral Vibe CLI. [1, 2, 3, 4, 5]Method 1: Using Ollama for Chat & General TasksOllama is a command-line tool that lets you pull and run large language models offline. [1, 2, 3]Step 1: Install Ollama [1]macOS & Windows: Download the application directly from Ollama.
[1, 2, 3, 4, 5]
Linux: Open your terminal and run the following command:bashcurl -fsSL
bashhttps://ollama.com
bash| sh
Step 2: Pull the Model
Open your terminal or command prompt and pull the specific Mistral or Llama version you want to use: [1, 2, 3]bashollama run mistral
# or for Llama 3
ollama run llama3
Step 3: Chat in the Terminal
Once the download is complete, the model will launch an interactive chat directly in your command line. You can type your prompts, ask questions, and exit by typing /bye. [1, 2, 3, 4, 5]Method 2: The Mistral Vibe CLI (For Coding & Agents)If you are focused on software development and coding, Mistral offers the Mistral Vibe CLI. It allows you to run powerful open-weight coding models (like Devstral) and perform codebase edits right from the command line. [1, 2, 3, 4, 5]Install the CLI using your terminal by following the guidelines on the Mistral AI Documentation.
Configure your API key.
Execute autonomous agent tasks and edit files directly via natural language instructions in your terminal. [1, 2, 3]
Further Exploration: Local LLM Tools & OptionsRun Mistral models through your terminal easily using the methods outlined in Simon Willison’s Weblog.
Learn the complete setup of Mistral 7B on macOS using llama.cpp via Medium.
Explore a step-by-step tutorial for deploying locally on macOS over at Medium. [1, 2, 3, 4]
📷📷📷8 sites
18 Dec 2023 — There are many ways to run Mistral models in your terminal using LLM: * **Using LLM command-line tools** * **Mixtral 8x7B via llam...Many options for running Mistral models in your terminal using LLM📷📷Simon Willison’s Weblog
9 Dec 2025 — | Mistral AI. ... The most powerful AI platform for enterprises. Customize, fine-tune, and deploy AI assistants, autonomous agents...Introducing: Devstral 2 and Mistral Vibe CLI. | Mistral AI : r/LocalLLaMA📷📷Reddit·r/LocalLLaMA
Install the Vibe CLI Install the CLI, configure your API key, and send your first prompt from the terminal.Mistral AI Documentation📷📷Mistral AI DocumentationShow all
Palantir from terminal? Apollo has an official CLI (including experimental debug terminal) and Foundry offers foundry-dev-tools for local pipeline simulation. It's enterprise-grade though—not a quick pip install like the separate single-cell bioinformatics package mixed into that quote.
DeepSeek? Easy yes—run their open models locally via Ollama, vLLM or similar in terminal. Solid for inference.
Karp nailed the tokenmaxxing critique: skip wasteful burn, choose what actually delivers value for your use case. What's the goal?
To run @PalantirTech from a terminal, your exact command depends on whether you are using the single-cell trajectory (scRNA-seq) algorithm, the Palantir Foundry platform SDK, or Palantir Apollo.Depending on your specific Palantir application, run one of the following terminal commands:Palantir (Single-cell RNA-seq Python package): Launch a Python environment and execute the function using:pythonimport palantir
pr = https://t.co/TZFune8XYi_palantir(data, early_cell="Your_Start_Cell")
Palantir Foundry (SDK): Use the official Foundry Platform SDK or standard Python terminal to simulate pipelines:bashpip install foundry-dev-tools
python your_pipeline_script.py
Palantir Apollo: Access the CLI and connect to your Apollo environment:bash./apollo-cli terminal --environment <environment-id>
Further Exploration:Check out the Palantir Read the Docs for a complete biological workflow https://t.co/lzZNkcOKPl the Palantir Apollo Debugging documentation for more on launching interactive Kubernetes debug terminals.Learn to simulate pipelines locally using the Palantir Python Local Development Guide.
To run @PalantirTech from a terminal, your exact command depends on whether you are using the single-cell trajectory (scRNA-seq) algorithm, the Palantir Foundry platform SDK, or Palantir Apollo.Depending on your specific Palantir application, run one of the following terminal commands:Palantir (Single-cell RNA-seq Python package): Launch a Python environment and execute the function using:pythonimport palantir
pr = https://t.co/TZFune8XYi_palantir(data, early_cell="Your_Start_Cell")
Palantir Foundry (SDK): Use the official Foundry Platform SDK or standard Python terminal to simulate pipelines:bashpip install foundry-dev-tools
python your_pipeline_script.py
Palantir Apollo: Access the CLI and connect to your Apollo environment:bash./apollo-cli terminal --environment <environment-id>
Further Exploration:Check out the Palantir Read the Docs for a complete biological workflow https://t.co/lzZNkcOKPl the Palantir Apollo Debugging documentation for more on launching interactive Kubernetes debug terminals.Learn to simulate pipelines locally using the Palantir Python Local Development Guide.