50 Best Tweets About Ollama (2026)

Find the best tweets about Ollama, including local model setup, performance, hardware, integrations, model files, and developer workflows.

Hands-on Ollama setup, local inference, supported models, integrations, performance, troubleshooting, and releases.

Creators
39
Updated

What 50 top Ollama posts reveal

Across 50 tweets, discussion is mostly supportive (86%) and positive (78%). The largest theme is models and local inference (46% of tweets), followed by agent and developer integrations (36%). The cited posts concentrate on practical local setups, compatibility layers, and local-first applications, while performance and hardware claims vary by model, backend, and platform.

Dominant tone
Positive

78% of posts

Median score
12.1

All-time engagement

Leading format
Announcement

52% of posts

Recent posts
38%

Published in 90 days

Conversation map

The themes creators return to

Tone and stance

Sentiment Positive leads
Author posture Supportive leads

Performance benchmark

Median likes
37
Median reposts
6
Median replies
5
Median views
3.8K

Posts with media make up 72% of this collection. Their median all-time score is 13.9, compared with 2.05 for text-only posts.

Format mix

  • Announcement 52% · score 12.3
  • Tutorial 34% · score 12.4
  • Opinion 10% · score 6.14
  • Case Study 2% · score 0.27

Where creators agree, and where they do not

Shared view

Local models are presented as usable workflows

Posts with concrete examples present Ollama as part of a local workflow: a Gemma setup, Anthropic Messages API compatibility for Claude Code-style workflows, and a Discord bot walkthrough using Gemma, OpenClaw, and Ollama.

Shared view

Compatibility layers are a recurring setup pattern

Integration examples focus on configuration and compatible interfaces: a localhost Anthropic-base-URL setup, Codex configured with Gemma through Ollama, and a chat UI that lists Ollama among supported OpenAI-compatible endpoints.

Shared view

Local-first applications emphasize offline operation

Several application posts emphasize local operation: CatchMe is described as offline with Ollama, Observer says screen-monitoring models can run through Ollama or llama.cpp without a cloud API seeing the screen, and World Monitor says its summaries run locally through Ollama without API keys.

Open debate

The local-versus-cloud boundary is debated

Posts differ on the practical boundary between local and cloud use. One argues that running GLM-5 locally requires expensive hardware and favors Ollama Cloud; another proposes Gemma 4 through Ollama for routine OpenClaw work while retaining Claude Opus for complex work. A third reports plans to compare OpenClaw with 4o mini and local Qwen 3B.

Open debate

Performance reports vary by backend and hardware

Backend reports are platform-specific and not fully aligned. One post ranks Ollama below llama.cpp and vLLM for its intended setup, Ollama’s post says its MLX update makes it faster on Apple Silicon, and another reports GPU-detection problems with Ollama on DGX Spark.

Patterns behind standout posts

Top engagement outliers combine platform news with actionable setup

The five deterministic engagement outliers are an Apple Silicon update, a Gemma local-run guide, Anthropic Messages API compatibility, Codex configuration with Ollama, and a Discord setup walkthrough. Four are tutorial or integration-oriented; the Apple Silicon post is an announcement.

Hardware fit is a recurring practical concern

Hardware-fit posts repeatedly foreground memory, quantization, and model choice. One author recommends a 64GB Mac Mini M4 Pro, a hardware-scanner post describes ranking models and quantizations against local specifications, and another reports running Qwen 3.5 9B through Ollama on a 16GB GPU.

Speed claims need workload and platform context

The cited speed figures and claims cover different contexts: Hermes Agent startup changes involving Ollama probes, Ollama Cloud throughput and latency on B300 hardware, and an Apple Silicon MLX comparison. They should be read as context-specific reports, not a single benchmark.

Statistical standouts

  1. View standout post 1 Score 1485.8 · 122.59× median
  2. View standout post 2 Score 1365.9 · 112.7× median
  3. View standout post 3 Score 955.9 · 78.87× median
  4. View standout post 4 Score 546.9 · 45.12× median
  5. View standout post 5 Score 282.3 · 23.29× median

Who shapes this conversation

The five most represented creators account for 20% of the selected posts.

  1. 1. Alex Veremeyenko

    @alex_verem

    2 posts

  2. 2. AlphaSignal AI

    @AlphaSignalAI

    2 posts

  3. 3. BowTiedCyber | Evan Lutz

    @BowTiedCyber

    2 posts

  4. 4. Fahd Mirza

    @fahdmirza

    2 posts

  5. 5. Ihtesham Ali

    @ihteshamali

    2 posts

  6. 6. Julian Goldie SEO

    @JulianGoldieSEO

    2 posts

Official posts highlight platform updates

Ollama’s two cited posts announce platform changes: MLX-backed Apple Silicon performance work and B300 cloud hardware for Kimi K2.5 and GLM-5. The latter post also says Ollama integrations can use its launch command and GitHub integrations.

Applied local AI is a recurring creator focus

Alex Veremeyenko’s two cited posts cover applied local systems: Observer for monitoring inputs such as screens and cameras, and World Monitor for locally summarized situational-awareness feeds.

How this analysis was made

Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.

Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.

This report analyzes the exact 50-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.

Top Ollama tweets from 39 creators

Ranked 01–50

  1. 01

    @ollama ·

    Ollama is now updated to run the fastest on Apple silicon, powered by MLX, Apple's machine learning framework. This change unlocks much faster performance to accelerate demanding work on macOS: - Personal assistants like OpenClaw - Coding agents like Claude Code, OpenCode, or

    Video thumbnail from ollama's post Watch video
    • 281 Replies
    • 720 Reposts
    • 5.7K Likes
    • 724.5K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  2. 02

    @EXM7777 ·

    here's how to run Gemma 4 locally in under 5 minutes: option 1 (phone): > download Google AI Edge Gallery from the Play Store > select Gemma 4 E2B or E4B > it downloads and runs entirely offline > no account, no API key, no internet needed option 2 (laptop): > install Ollama or

    • 37 Replies
    • 149 Reposts
    • 1.7K Likes
    • 113.3K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  3. 03

    @akshay_pachaar ·

    this is huge. ollama is now compatible with the anthropic messages API. which means you can use claude code with open-source models. think about that for a second. the entire claude harness: - the agentic loops - the tool use - the coding workflows all powered by private LLMs

    • 149 Replies
    • 228 Reposts
    • 2.2K Likes
    • 164.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  4. 04

    @skirano ·

    I love how open the Codex app is, you can run any model you want, even local. These are the only configs you need to use the app with Gemma 4 via Ollama.

    Video thumbnail from Pietro Schirano's post Watch video
    • 51 Replies
    • 59 Reposts
    • 1.3K Likes
    • 114.7K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  5. 05

    @fahdmirza ·

    Gemma 4 + OpenClaw + Ollama + Discord — Full Local AI Setup for Free 🔥 Google just dropped Gemma 4 and we wired it directly into Discord 🔹 Gemma 4 31B pulled via Ollama — completely local 🔹 Fresh OpenClaw install from scratch 🔹 Full Discord bot setup — Developer Portal,

    • 5 Replies
    • 38 Reposts
    • 359 Likes
    • 23.2K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  6. 06

    @Axel_bitblaze69 ·

    many of you keep asking me in the comments what machine to buy for AI I run Claude Code, Ollama with local models, MCP servers, Paperclip agents, Chrome automation, and way much more and screen recording all at the same time.. after testing everything tbh, the Mac Mini M4 Pro

    • 64 Replies
    • 64 Reposts
    • 688 Likes
    • 125.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  7. 07

    @charliejhills ·

    🚨Stop gambling on the wrong local LLM. Most people download a model, watch it crawl, then start over. LLM Hardware Scanner is a CLI tool that scans your actual specs and ranks hundreds of LLMs before you waste the bandwidth: ⤷ Reads your RAM, CPU, and GPU to score real

    Video thumbnail from Charlie Hills's post Watch video
    • 19 Replies
    • 45 Reposts
    • 304 Likes
    • 37.4K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  8. 08

    @support_huihui ·

    When using the free-code mode with a local model, set the following three parameters. export ANTHROPIC_BASE_URL=http://localhost:11434 export ANTHROPIC_AUTH_TOKEN=ollama export ANTHROPIC_API_KEY="" free-code -p "hello" --model xxx https://t.co/ubjnB9rBiJ

    • 8 Replies
    • 17 Reposts
    • 167 Likes
    • 10.5K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  9. 09

    @ollama ·

    Ollama's cloud is updated to use NVIDIA's latest data center hardware: B300 for Kimi K2.5 and GLM-5 models. This significantly improves the model performance with faster throughput and lower latency while maintaining reliable tool calls for integrations. All this works with

    I love Ollama's cloud. I hope you do too!
    • 54 Replies
    • 41 Reposts
    • 674 Likes
    • 42K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  10. 10

    @ihteshamali ·

    Someone just built Windows Recall but its open source, local, and actually private. It's called CatchMe. It records everything you do on your computer and lets you search it in plain English. No cloud. No subscriptions. No data leaving your machine. Here's what it tracks

    • 4 Replies
    • 20 Reposts
    • 114 Likes
    • 4K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  11. 11

    @VaibhavSisinty ·

    I just discovered the free version of Claude Code. It is called opencode and it is crazy good. Best part? Open source. And the most starred coding agent on GitHub right now. Install it in 60 seconds: → curl -fsSL https://t.co/2QSqHlbvg4 | bash That is it. One line. Done.

    Video thumbnail from Vaibhav Sisinty's post Watch video
    • 20 Replies
    • 11 Reposts
    • 128 Likes
    • 8.8K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  12. 12

    @RaulJuncoV ·

    The agent loop controls your entire stack. How your model sees tools. How it retries. How it handles context. Most developers can't touch it. You need hooks. The runtime doesn't expose them, so you wrap it. You swap providers. The abstraction leaks, so you patch it. Three

    • 6 Replies
    • 11 Reposts
    • 79 Likes
    • 5.8K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  13. 13

    @DataChaz ·

    💡 Tip If you only have a 16GB GPU: you can run Qwen 3.5:9b locally via Ollama. - Unbelievable 130 t/s throughput - Perfect for straightforward, common tasks Use frontier models for planning, then hand off to Qwen for the rest! ;)

    • 13 Replies
    • 22 Reposts
    • 139 Likes
    • 11.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  14. 14

    @Sumanth_077 ·

    Train LLMs locally without writing a single line of code! @UnslothAI just released Unsloth Studio - an open-source web UI for training and running models. Here's how it works: You upload a PDF, CSV, or DOCX file. The Data Recipes feature automatically transforms it into a

    Video thumbnail from Sumanth's post Watch video
    • 5 Replies
    • 23 Reposts
    • 67 Likes
    • 4.3K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  15. 15

    @alex_verem ·

    Found an open source tool that watches your screen and pings you when something happens. It's called Observer. You build tiny AI agents that monitor your screen, camera, or mic with a local model, then react. Your training run crashes, you get a Telegram message. A dashboard

    • 12 Replies
    • 20 Reposts
    • 69 Likes
    • 4.9K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  16. 16

    @tonysimons_ ·

    Hermes Agent just got a serious speed injection. First-turn startup latency was cut by ~80%. Cold submit → request dispatch: 4.3s before 0.9s after The fix? @Teknium tracked the actual pre-request stalls and cut them out: 🔹 Discord capability detection moved off the

    • 10 Replies
    • 6 Reposts
    • 89 Likes
    • 4.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  17. 17

    @hasantoxr ·

    Anthropic Fable 5 has been banned by the government. Learn to use local models so you have 100% control. Instead of arguing about why they banned it, I built a full guide on running AI locally so nobody can ever take it from you. Here's everything you need to know: 1. Pick

    • 9 Replies
    • 2 Reposts
    • 62 Likes
    • 6K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  18. 18

    @itsharmanjot ·

    GitHub is shutting down its entire AI playground on July 30, 2026. Playground. Model catalog. Inference API. BYOK. All of it. Gone for every customer including people with active usage right now. What GitHub Models was: Free access to Llama 3.1, GPT-4o, Mistral, Cohere

    Video thumbnail from Harman's post Watch video
    • 9 Replies
    • 11 Reposts
    • 48 Likes
    • 8.7K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  19. 19

    @alex_verem ·

    World Monitor is an open-source situational awareness dashboard that puts military, economic, climate, and financial signals in one view. It ingests 500+ news feeds across 15 categories and summarizes each item with AI as it arrives. The feeds cover military movements, economic

    • 12 Replies
    • 6 Reposts
    • 34 Likes
    • 3.6K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  20. 20

    @VaibhavSisinty ·

    I've been saying this for a while now. The future isn't one massive model sitting in the cloud doing everything for you. It's tiny specialist models running on your device. Doing 80% of tasks locally. A small router model deciding which model handles what. And only pinging

    Video thumbnail from Vaibhav Sisinty's post Watch video
    • 3 Replies
    • 15 Reposts
    • 65 Likes
    • 4.4K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  21. 21

    @ayushagarwal ·

    contextmcp v0.5.0 just shipped. contextmcp is our open-source MCP server that indexes your documentation and serves it as context to AI agents. point it at your docs repo, it chunks, embeds, and gives your agent the right documentation when it needs it. what's new: → Ollama

    Video thumbnail from Ayush Agarwal's post Watch video
    • 8 Replies
    • 3 Reposts
    • 49 Likes
    • 2.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  22. 22

    @Shruti_0810 ·

    Someone just broke the Claude paywall… for real. Claude Code → $0 API key → $0 usage cost Here’s what they built: A tiny proxy that hijacks Claude Code’s API and reroutes it to free + local models • NVIDIA NIM (free tier) • OpenRouter (hundreds of models) • DeepSeek

    • 8 Replies
    • 6 Reposts
    • 27 Likes
    • 2.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  23. 23

    @ihteshamali ·

    A community of 300 anonymous developers built the AI companion Character AI's investors are afraid of. It's called SillyTavern. This is the app Character AI users switched to when the platform banned NSFW content in 2024, Replika users moved to after the company deleted

    • 6 Replies
    • 8 Reposts
    • 24 Likes
    • 3.6K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  24. 24

    @GithubProjects ·

    Chat UI is a SvelteKit chat interface that works with any OpenAI-compatible API, powering HuggingChat at https://t.co/3Q2b7hKvgg. - Connects to any OpenAI-compatible endpoint via OPENAI_BASE_URL and /models - Supports llama.cpp, Ollama, OpenRouter, and the Hugging Face Inference

    • 0 Replies
    • 6 Reposts
    • 61 Likes
    • 11K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  25. 25

    @_vmlops ·

    OLLAMA-OCR TURNS YOUR SCANNED DOCS INTO CLEAN MARKDOWN built on top of ollama's local vision models, no cloud APIs, no OCR subscriptions → swap between llava, llama 3.2 vision, granite3.2-vision, moondream, minicpm-v depending on speed vs accuracy needs → output as markdown,

    • 1 Replies
    • 7 Reposts
    • 27 Likes
    • 2K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  26. 26

    @socialwithaayan ·

    you can now hand your entire to-do list to an AI coworker that runs on your laptop and actually does the work 🤯 it's called OpenWorker. andrew ng built it. the man who founded google brain, ran AI for 1,300 people at baidu, and co-founded coursera. this is not another chatbot.

    • 22 Replies
    • 3 Reposts
    • 42 Likes
    • 7K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  27. 27

    @smratitiwa86867 ·

    Google just open-sourced a tool that could replace an entire category of document extraction software. Content: It's called LangExtract. An open-source library designed to turn messy, unstructured documents into structured data—with source references you can verify. What it

    • 5 Replies
    • 6 Reposts
    • 17 Likes
    • 1.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  28. 28

    @thetripathi58 ·

    You need an AI pair programmer to write boilerplate, debug logic, and speed up execution. What are your options? GitHub Copilot sends your proprietary codebase to Microsoft servers to feed their massive models. ChatGPT requires you to paste your sensitive intellectual property

    Video thumbnail from Chidanand Tripathi's post Watch video
    • 6 Replies
    • 17 Reposts
    • 40 Likes
    • 10.3K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  29. 29

    @metasploit ·

    Latest Metasploit update is out with unauthenticated RCE for Grandstream GXP1600 VoIP devices, enabling credential harvesting and SIP interception. Also included is critical support for BeyondTrust PRA/RS command injection (CVE-2026-1731), plus a serious Ollama RCE

    • 0 Replies
    • 14 Reposts
    • 44 Likes
    • 5.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  30. 30

    @AlphaSignalAI ·

    Stop downloading LLMs your machine was never going to run. llmfit scans your hardware and tells you exactly which models will run. It scans your RAM, CPU, GPU, and VRAM first. Then it scores every model across four dimensions: 1. Quality, based on parameter count and

    Video thumbnail from AlphaSignal AI's post Watch video
    • 3 Replies
    • 4 Reposts
    • 9 Likes
    • 650 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  31. 31

    @NainsiDwiv50980 ·

    Your agentic AI product can earn its first dollar before it generates its first model API bill. Not a toy chatbot. A real system that retrieves knowledge, makes decisions, calls tools, takes actions, retains state, and traces what happened, running on a stack that costs exactly

    • 2 Replies
    • 3 Reposts
    • 10 Likes
    • 1.3K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  32. 32

    @BowTiedCyber ·

    The local vs cloud AI debate is an absolute joke Running GLM5 locally takes tens of thousands of dollars in hardware Ollama cloud is $20/month You won’t get the same reasoning out of qwen7b Just admit that the tech isn’t there yet The $20 is worth it

    • 9 Replies
    • 1 Reposts
    • 14 Likes
    • 1.5K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  33. 33

    @RoundtableSpace ·

    Ornif 1.0 is a free local model running through Ollama that's reportedly beating models 10x its size. It writes its own plan before coding, then grades itself on both the strategy and the output.

    Video thumbnail from 0xMarioNawfal's post Watch video
    • 5 Replies
    • 3 Reposts
    • 62 Likes
    • 32.3K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  34. 34

    @vectro ·

    Figuring out a good setup for local LLM in Hermes Agent using the OpenAI compatible endpoint A few local inference systems support this From what I can see, in order of efficiency from worst to best... * Ollama * llama.cpp * vLLM (what I'll try) Will make a video tutorial.

    • 1 Replies
    • 1 Reposts
    • 9 Likes
    • 306 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  35. 35

    @RoundtableSpace ·

    15 minutes of Kimi Code beats 10 hours of reading docs. Covers Claude Code with Ollama, web search, scheduled tasks, Telegram integration, and headless mode. The docs never had a chance.

    Video thumbnail from 0xMarioNawfal's post Watch video
    • 5 Replies
    • 1 Reposts
    • 23 Likes
    • 16.1K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  36. 36

    @SaiyamPathak ·

    Ollama just replaced launched 0.19 with Apple's MLX framework on Apple Silicon. The result? ~2x faster inference as per there test on M5 I tested it on my M1 Max the difference is real. New video breaking down: → What MLX is and why it's faster → UMA explained → Prefill

    • 2 Replies
    • 2 Reposts
    • 16 Likes
    • 964 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  37. 37

    @JulianGoldieSEO ·

    𝗚𝗼𝗼𝗴𝗹𝗲'𝘀 𝗚𝗲𝗺𝗺𝗮 𝟰 𝗿𝘂𝗻𝘀 𝗳𝗿𝗲𝗲 𝗼𝗻 𝘆𝗼𝘂𝗿 𝗹𝗮𝗽𝘁𝗼𝗽 𝗮𝗻𝗱 𝗿𝗮𝗻𝗸𝗲𝗱 𝗻𝘂𝗺𝗯𝗲𝗿 𝟯 𝗶𝗻 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱 𝗼𝗻 𝗮𝗻 𝗼𝗽𝗲𝗻 𝗺𝗼𝗱𝗲𝗹 𝗹𝗲𝗮𝗱𝗲𝗿𝗯𝗼𝗮𝗿𝗱. No subscriptions. No data leaving your machine. No internet needed once it's set up. Here's which model to pick and how to run it: → Standard laptop: ollama run gemma4:e4b

    Video thumbnail from Julian Goldie SEO's post Watch video
    • 0 Replies
    • 2 Reposts
    • 8 Likes
    • 525 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  38. 38

    @BowTiedCyber ·

    I’ll be testing 2 things today: OpenClaw with 4o mini OpenClaw with local Qwen:3b Setup: Linux VM Bridged adapter Ollama running host with 32gb ram and 12gb GPU Testing with ollama cloud was good but token burn rate was heavy

    • 1 Replies
    • 0 Reposts
    • 10 Likes
    • 511 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  39. 39

    @DomJoLuna ·

    Everybody's panicking about Anthropic cutting off OpenClaw today. A lot of people are switching to OpenAI as their default model, and to be frank, that's a downgrade you don't need to make. Here's what's actually happening…Anthropic is separating subscription limits from

    • 1 Replies
    • 1 Reposts
    • 3 Likes
    • 118 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  40. 40

    @AlphaSignalAI ·

    Someone open-sourced a survival computer that works even when the internet goes down. Project N.O.M.A.D turns any Linux machine into a fully offline knowledge server. No internet needed after setup. The AI runs through Ollama. You can chat, write, and code locally. Upload

    • 2 Replies
    • 0 Reposts
    • 2 Likes
    • 407 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  41. 41

    @ThePracticalDev ·

    Gemma 4 12B runs on a standard 16GB laptop thanks to Quantization-Aware Training. This tutorial walks through building a fully offline visual AI agent with Python and Ollama. { author: @leslysandra + @GoogleDevExpert } https://t.co/X60OI4zb42

    • 1 Replies
    • 3 Reposts
    • 13 Likes
    • 3K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  42. 42

    @cleanunicorn ·

    I am a total self hosting nerd. Currently I am away from my computer, but I still have access to my servers. I can run consumer grade (not mobile grade) LLMs on my local setup using: - Tailscale - for access (VPN) - Open WebUI - chatGPT-like interface for LLMs - Ollama - LLM

    • 2 Replies
    • 1 Reposts
    • 17 Likes
    • 1.9K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  43. 43

    @fahdmirza ·

    💥 Hermes Agent is the AI that gets smarter every session ⚕ ♠ and it's completely changing what a local self-improving agent looks like 🚀 🔹 Built by Nous Research — the lab behind some of the most capable open source models 🔹 Closed learning loop — creates skills from experience

    • 1 Replies
    • 0 Reposts
    • 2 Likes
    • 496 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  44. 44

    @JeremyCMorgan ·

    A concrete local AI coding stack instead of vague "run models locally" advice. Ollama backend, OpenCode shell, Chrome DevTools and GitHub MCP as tools, with model picks by hardware (GLM-4.7-Flash vs Qwen3-Coder). A baseline to benchmark your setup against.

    • 1 Replies
    • 0 Reposts
    • 4 Likes
    • 196 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  45. 45

    @PawelHuryn ·

    Lemonade just hit v10 — an open source local AI server backed by AMD, designed to compete with Ollama. I tested it on my laptop (RTX 2000 Ada, 8GB VRAM). Here's what actually happened. 🧵

    • 2 Replies
    • 1 Reposts
    • 3 Likes
    • 705 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  46. 46

    @WesRoth ·

    Ollama has officially added image generation capabilities now live for macOS, with support for Windows and Linux coming soon. Users can generate photorealistic or stylized images right from their terminal using models like: Z-Image Turbo (from Alibaba’s Tongyi Lab): great at

    • 0 Replies
    • 0 Reposts
    • 8 Likes
    • 883 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  47. 47

    @JulianGoldieSEO ·

    𝗥𝘂𝗻 𝗚𝗼𝗼𝗴𝗹𝗲'𝘀 𝗚𝗲𝗺𝗺𝗮 𝟰 𝗹𝗼𝗰𝗮𝗹𝗹𝘆 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲 𝗶𝗻 𝗺𝗶𝗻𝘂𝘁𝗲𝘀 𝘂𝘀𝗶𝗻𝗴 𝗢𝗹𝗹𝗮𝗺𝗮. Ranked number 3 in the world among open models. Runs on your laptop. No cloud. No data leaving your machine. Here's exactly which model to pick: → E4B (9.6GB): Start here if you're on a typical laptop. Run: ollama

    Video thumbnail from Julian Goldie SEO's post Watch video
    • 0 Replies
    • 0 Reposts
    • 0 Likes
    • 174 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  48. 48

    @PsudoMike ·

    Jeff Morgan and Michael Chiang met at Waterloo, built Kitematic, and sold it to Docker, and that work is still the backbone of Docker Desktop today. Now they've raised $65 million USD for Ollama, an open source tool for running AI models on your own machine instead of renting

    • 0 Replies
    • 1 Reposts
    • 3 Likes
    • 751 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  49. 49

    @SaiyamPathak ·

    my DGX spark fan in full force! Gemma results will be shared in a few Ollama for DGX spark don't run properly as it won't detect the GPU - vllm is the best for now - I am also running their llama cpp playbook will share the results shortly the the video dropping on gemma 4 soon!

    • 0 Replies
    • 0 Reposts
    • 6 Likes
    • 560 Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.
  50. 50

    @ThePracticalDev ·

    Hit a Claude usage limit mid commit, so this dev built a local LLM setup with Ollama for git messages, with Claude as a fallback option. { author: @shyamala_u } https://t.co/8midG65ZBe

    • 0 Replies
    • 0 Reposts
    • 9 Likes
    • 2.4K Views
    View on X
    Rewrite this post in your own voice and angle. See the hook, structure, and reusable template behind this post.

Explore more of the best tweets on X.

Browse all tweet collections

Tweet Remixer

Remix this post

Creator

@creator

View on X

Choose a tone