Help Me Find the Best Free AI for the Computer You Already Have

Table of Contents
2
7

I first really saw the digital divide in 2019, when I was working at GreenLeaf Market in St. Louis. That job was pivotal to my growth as a professional adult. The store was a melting pot: people from the neighborhood, people from the North Side, and people from the St. Louis Public Schools administration building nearby, who would tell me about what their students were up against in different parts of town.

Through all of those conversations, I became very aware of the digital divide. Food insecurity was a big part of it too, and that’s another passion of mine (I have to choose my battles, I guess). But beyond food, a lot of these families were living with this: maybe they got cheap broadband through a government program. They probably had an older computer, or one that ended up breaking. It definitely didn’t have a high-end graphics card. It was probably the cheap Walmart laptop or PC they bought with their tax refund, a little extra child support, or the money from selling the beat-up old car after it broke down and they started taking the bus.

It doesn’t matter how. What matters is that this is real life for a lot of people, people I met myself and people I heard about secondhand. And it made me think: what about the kids? It’s hard enough to look for a job on a public library computer. What kind of disadvantage is this giving the kids?

The numbers back up what I was hearing. A 2022 report for the St. Louis Community Foundation and the Regional Business Council estimated that a quarter of households in the City of St. Louis had no computer or only a smartphone. Nationally, Pew Research Center found in 2018 that 17% of teens were often or sometimes unable to finish their homework because they didn’t have a reliable computer or internet connection. For teens in households earning under $30,000, it was 24%.

Now, in 2026, AI is one more layer on top of all that. Say you’re getting online from an older iPhone, a 7 or an 8 if you’re lucky, or a cheaper Android phone. You don’t have affordable broadband, you’re not sharing Wi-Fi with a neighbor, and you don’t want to go to the library, because you need the internet at 11 p.m., after your kids are in bed. Or, if you’re a teenager, after your little brothers and sisters have finished their homework. That’s a reality for a lot of people.

And people are stressed out. I think a lot of people believe that poor people are poor because they make bad decisions. But when you’re living with the daily grind of stress just to stay alive and keep a roof over your head, it takes a toll on your ability to think and decide. That’s not just my opinion. In a 2013 study published in Science, lower-income people did worse on cognitive tests after being asked to think about paying for a $1,500 car repair, and sugarcane farmers in India did worse before harvest, when money was tight, than after it. The researchers compared the effect to losing about 13 IQ points, or a full night’s sleep. As one of them put it, “It’s not about being a poor person — it’s about living in poverty.”

All of this feeds into bigger problems: poverty, food insecurity, housing insecurity, the growing gap between rich and poor, and a middle class that keeps getting shakier. I could go off on a political tangent here, but I won’t. This post is about one piece of it: the AI divide, and the job skills and tech literacy our younger generations need. And not just kids. Young adults and older adults are getting phased out by AI too. Nobody should be left behind when it comes to jobs, the skills of the future and the technology we already have.

That’s where this project comes from. Last week I published the results of generating a full 30-chapter book with a free AI model on an 8 GB budget laptop. The short answer: yes, you can, if you’re patient. That answered one question and raised a bigger one. What’s the best AI a regular person can run on the computer they already have, without paying for anything?

I wrote a plan to find out, and I’m publishing it before I run it: the questions, the tests, the bar each model has to clear and what would prove me wrong. You can download it as a PDF, poke holes in it, and, if you’d like, run part of it on your own computer and add your results to mine.

What I’m trying to find out

Three things, in this order:

  1. The best local model for long-form writing on my main computer, which has an RTX 4070 graphics card. This is the one I’ll use myself.
  2. The best local model for a consumer-grade laptop like my ASUS Vivobook: a Core i3, 8 GB of memory and no graphics card. This is the one that matters most to me, because it’s the one most of my readers can actually use.
  3. The best budget-friendly model you can reach over the internet, most likely an open-weight model on OpenRouter, a service that lets you pay per use for hundreds of models through one account.

My hypothesis is that even the bigger models my 4070 can run can’t yet match the large hosted models, whether through OpenRouter or straight from Claude, ChatGPT and Gemini. The plan spells out what would prove me wrong, and I’ll lock that bar into the results sheet before the hosted tests start, so I can’t move it afterwards.

If I’m right, it supports a letter I plan to write to Stripe and OpenRouter (Stripe agreed to buy OpenRouter in August). I’ll be asking for something like Google Ad Grants, but for AI: free credits for schools, nonprofits and students. A free local model can get someone a draft. Affordable access to a strong hosted model could get them a good one.

Why the computer you already have

Most AI benchmarks are run on hardware most people will never own. The people I want this to help are on a phone, a budget laptop, or an older computer running off a phone’s hotspot.

The numbers back that up. In Pew Research Center’s 2025 survey, 34% of adults in households earning under $30,000 had a smartphone but no home broadband, compared with 4% in households earning $100,000 or more. The Census Bureau’s 2024 American Community Survey counts about 17.7 million U.S. households with no desktop, laptop or tablet at all (as summarized by Digitunity).

And the AI divide is already showing up in who uses these tools. About half of U.S. adults live in households earning $100,000 or more, but in an Epoch AI and Ipsos survey this spring, 56% to 64% of weekly ChatGPT, Gemini, Copilot and Grok users did. For Claude, the AI I use most for this project, it was about 80%.

I’ve been here before. In 2024 I ran AI models on the same ASUS laptop with Open WebUI. It worked, but it took Docker, a Linux subsystem config file and a lot of patience. Two years later there are simpler apps, and small models have improved a lot. It’s time to test it properly.

The plan, in four parts

  • Part 1: book-length tests on my 4070. I’ll keep generating the same 30-chapter test book in BookyAI, one model at a time, and measure length, repetition and quality, with AI judges that don’t know which model wrote what.
  • Part 2: the laptop under a real-world load. The winners run on the ASUS the way people actually use their computers: antivirus running, Word and Notepad open, and 20 browser tabs.
  • Part 3: the apps. Ollama, LM Studio, Jan, AnythingLLM and Open WebUI, compared on what they need, how long setup takes, and whether someone who isn’t technical can get them working.
  • Part 4: cheap hosted models. The same prompts and scoring through OpenRouter and the big AI companies’ own services, with a spending cap on every account, so I can see what a few dollars buys.

The plan has the details: which models, in what order, what gets recorded, and the bar a model has to clear to move on.

Run it yourself

This is the part I’m most excited about, and it’s where this project parts ways with my BookyAI tests: it uses only free software, open source wherever possible. If you have a Windows, Mac or Linux computer with at least 8 GB of memory and about 10 GB of free space, you can take part. You don’t need a graphics card.

It would make a great project for a curious teenager, a classroom, a computer club, or anyone who has wondered whether “AI” has to mean a monthly subscription. Plan on an afternoon:

  1. Write down your computer’s specs.
  2. Install one free app: Ollama, Jan or AnythingLLM (all open source), or LM Studio (free, but not open source).
  3. Download one small model, picked from a short list by how much memory you have.
  4. Leave your computer the way you normally use it. Don’t close everything first.
  5. Run three short prompts: an email, a summary and the opening of a story.
  6. Send your results through a short form.

The full instructions, the exact prompts and the model list are in the plan. Every result goes into a public, read-only results sheet with names and email addresses removed. The form doesn’t require any personal information; leaving an email is optional. If you’re under 18, please ask a parent or guardian before installing anything.

How I use AI to do this

Yes, I’m using AI to teach me about AI, and I want to be upfront about how. I’m co-creating with AI, and I have been in some form for a while. I started in 2022 at eSpecial Needs, with a lifetime deal on Peppertype, rewriting social posts for different platforms. In 2023 I started using it more seriously for social posts and blog drafts, and by 2024 for personal development too.

For this project, I use Claude, mostly Claude Opus 5.5, to help me analyze results, write the scripts that measure repetition and timing, and draft and edit posts like this one. I use Google’s NotebookLM and AI Mode in Google Search for research and brainstorming, and I’ll likely bring in Gemini 3.1 Pro too. I check the numbers against my own run files and the original sources, and when something has been wrong, I’ve published the correction.

The values, the mission and the creativity are 100% from my very human brain.

Why I’m doing it this way

AI may end up destroying our world. But for right now, it’s here, and it’s the reality people are living in.

I may have idealistic values, but I always try to center them on one question: what resources do I have right now? Otherwise it’s so easy to get distracted by what-ifs, could-dos and should-dos. That’s something my arguments with my boyfriend have taught me. He is super-idealistic, which I always thought was a quality I had, but I’ve learned through our often heated discussions that I am really one of those people who’s primarily focused on the exigency and importance of now. Yes, in five years I might have a new car, or my job situation might be better. But right now, right here, what are the choices? What’s on my plate?

That’s what this experiment is. It may change in two weeks, or next week, or tomorrow after somebody gives me feedback, for all I know. But I’m working with what I know right now, on a Wednesday morning, with Claude and Google’s AI tools, my own creativity and my own life experience.

I see this as a teeny tiny part of a much bigger problem, one that can possibly be addressed, and researched in real life, through citizen science and collaborating with different people. And I’ll be the first one to say I’m wrong if I’m wrong.

That’s not just a nice thing to say. Not getting too attached to ideas has been one of my biggest resiliency skills. A little about me that I may not have shared: I moved out of the house as soon as I turned 17, back in 1997. Without getting into the details of my childhood, if you go by the research on adverse childhood experiences, my life could easily have gone a very different way. But I’ve been fortunate to have experiences that taught me resiliency, to be naturally inclined toward it, and to be born in the right time and the right place. Springfield, Missouri, in the late ’80s and early ’90s was a pretty good part of the country, and a lot less rough than some places. I made the best decisions I could with what was in front of me, and I think most people do.

Every coping skill has its shadow side and its benefits. There are probably some deeper issues behind not getting very attached to anything. But the benefit of not being attached to ideas is that I openly embrace new ones.

So please, correct me, collaborate with me, tell me I’m wrong, and tell me what I got right. Hopefully I got a few things right.

Get involved

If the answer turns out to be “the computer you already have is enough for a draft,” that’s worth knowing. If it’s “not yet,” that’s worth knowing too, and worth fixing.

Very humbly, this is what I’m putting out into the world. I think it could possibly make things better, and I think it’s maybe a good idea.

No affiliate links and no sponsored tests. I bought BookyAI and all software and equipment myself.

P.S. While I was finishing this post, LinkedIn shared its August report, The AI Talent Divide. The typical AI job posting lists $177,000, compared with $80,000 for non-AI roles, and about 91% of AI roles are held by people with a bachelor’s degree or higher. The easiest AI job in the report to get, data annotation, is also the lowest paid. And some of the easiest AI work of all isn’t counted in it: I’ve spent the past few weeks recording myself doing household chores to train AI robots. That’s a whole other post, coming soon.

PS – due to response from my readers and friends, I’ve included the experiment plan below so you don’t need to download the pdf or read it on Google Docs

Local AI experiment plan

Date last revised: Oct 21, 2026 · @Jessica Murray

This plan tests which AI writing setups a regular person can actually use, from a free model on an 8 GB laptop to cheap hosted models through OpenRouter, so the open letter rests on my own measurements.

How this plan was made: I’m building this in public and learning as I go. I use AI to help: Claude (mostly Opus 5.5) for data analysis, scripts and drafting, and Google’s Gemini Pro and Gemini notebook tools [CONFIRM the exact Gemini product names] for brainstorming and research. The values, the mission, the questions and the decisions are mine, and every number here comes from my own runs or a cited source. Feedback and corrections are welcome.

Goals and hypothesis

The plan answers three questions, in this order:

  1. The best local model for long-form writing on my 4070 (RTX 4070 12 GB, 128 GB RAM). This is the one I’ll use myself.
  2. The best local model on a consumer-grade laptop like my ASUS (Core i3-1215U, 8 GB RAM, no graphics card). This is the one my readers can use, and it’s the core of why I do this: the digital and AI divides as they look in real life.
  3. The best budget-friendly model through an API, most likely an open-weight model on OpenRouter.

Hypothesis: even the larger models my 4070 can run can’t yet match the larger hosted models available through OpenRouter or directly from Claude, ChatGPT and Gemini. If that holds, the argument for the open letter is: local AI gets a person a draft; affordable hosted access gets them a good one; and OpenRouter, which Stripe agreed to acquire on August 19, 2026, could put that access within reach of schools, nonprofits and students.

What would prove me wrong: a local model on the 4070 that scores within the judges’ noise of the best hosted model on the same prompt and rubric, with repetition under 1%. I’ll write the exact bar into the sheet before the hosted runs start, so I can’t move it afterwards.

Why it matters: who is actually online, and on what

A third of lower-income adults reach the internet only through a phone, and millions of households have no computer at all. Pew’s 2025 survey (5,022 adults, February to June 2025, published January 2026):

Household incomeUnder $30,00030,000-69,99970,000-99,999$100,000+
Smartphone but no home broadband34%19%10%4%
Home broadband subscription54%75%88%94%

Across all adults in Pew’s 2026 surveys (January to June 2026), 78% have home broadband and 16% are smartphone-only. The Census Bureau’s 2024 American Community Survey counts about 17.7 million U.S. households, 13.3%, with no desktop, laptop or tablet: 13.2 million with only a smartphone and 4.5 million with no computing device at all (as summarized by Digitunity).

What this means for the plan: the realistic reader is not on my 4070. They’re on a phone, a budget laptop, or a phone hotspot feeding an older computer. Two things I believe but have not yet sourced, and won’t state as fact until I do: that phone-dependent households are more likely to own older phones, and that the computers in lower-income homes are mostly budget or older machines without a gaming graphics card.

Phase 1: BookyAI model sweep on the 4070

Note: This part is my personal experiment towards saving myself money on API usage, and my own creative outlet.

Find the best local model for long-form writing, using the 4070 as the screening machine, since in my Gemma runs so far, the machine changed how long a book took far more than what it wrote.

Held still for every run: BookyAI 1.9.24 (don’t update mid-sweep), the Affirmation Glitch control prompt at 30 chapters of 3,000 words, 8,192 context set in both BookyAI and Ollama (check ollama ps CONTEXT during the run), thinking off, “stay on my engine” on, a neutral project title, and manual outline approval with blank outlines counted.

The bar on 1.9.24: gemma4:e4b (N1-8k-r3) wrote 106% of target at 1.3% repetition with no decay, and scored 13/50 with the judge (not blind). gemma4:26b scored best so far, 23/50, but on 1.9.23.

Queue, in order:

  1. gemma4:26b on 1.9.24. The current best, run again on the new version so it’s a fair reference.
  2. gemma4:e2b (4.6 GB). The smallest Gemma, a laptop candidate.
  3. qwen3.5:4b and qwen3.5:9b, already downloaded. Turn thinking off first.
  4. gpt-oss:20b, a mixture-of-experts model. Check its reasoning effort setting first; the earlier run on the 2060 crawled.
  5. laguna-xs-2.1, a mixture-of-experts model with about 3B active parameters. Never run.
  6. qwen3.8:27b (18 GB). 4070 only; it will spill out of the card’s memory.
  7. Community picks from the BookyAI group and Ollama’s library, filtered by download size.

Promote a model to the laptop (Phase 2) only if it clears all of these: length 90% to 110% of target, repetition at or under 1.5%, no chapter over 30% self-repetition, chapters 21-30 at least 0.9 of chapters 1-10, and a blind judge score at or above e4b’s. I’ll write these into the sheet before the first run.

Blueprint arm (after the sweep): freeze one blueprint for the Affirmation Glitch, publish it beside the control prompt, and run the top two models with the bare prompt and with the blueprint. That measures what a blueprint is worth, separately from which model is best.

Phase 2: the laptop under a real-world load

Run the models that pass Phase 1 on the ASUS the way a normal person would use it: with other programs open.

Candidates: whatever passes Phase 1 and fits the laptop. gemma4:e4b already ran there; gemma4:e2b, qwen3.5:4b and qwen3.5:2b are the likely others.

The real-world load profile, set up the same way before every run:

  • Windows 11 Home, plugged in, sleep and screen-off disabled
  • AVG Free running
  • Word open with one document
  • Notepad open with one note
  • 20 browser tabs from a fixed saved list

Record before each run: free memory in Task Manager, plus the “available” figure in Ollama’s log when it starts. On one model, run once clean and once loaded, so the cost of the load is measured, not assumed. Ollama reported 1.3 GB free on one morning and 430 MB on another, so this matters.

Record during each run: restarts, hands-on minutes (each time I have to check on it or press Regenerate), and failed requests from Ollama’s server.log. A failure at about 5 minutes is BookyAI’s first-response wait expiring.

Before Phase 2, find out whether the ASUS RAM is soldered. If there’s a free slot, 16 GB is a cheap upgrade, and “what a small upgrade buys” is a story the divide argument can use.

Phase 3: platforms and wrappers

Find the app a non-technical person can install on the ASUS and actually use, and which of those can also connect to OpenRouter. The second part is the bridge the open letter needs: the same app that runs a free local model can switch to an affordable hosted one.

What each tool’s own documentation says (October 2026):

ToolWhat it isWindows installRuns models itselfOpenRouter / APIRequirements and notes
OllamaEngine, with a tray appInstaller, no admin rights neededYesNot documented; sells its own optional cloud planWindows 10 22H2 or newer; 4 GB for the program; models stored in your home folder unless OLLAMA_MODELS moves them
Open WebUIChat and documents surfaceDocker (recommended), Python pip/uv, or a native desktop app with no DockerThrough Ollama, or the desktop appConnects to any OpenAI-compatible API; OpenRouter not named, to testOpen WebUI License (source-available); my 2024 setup needed Docker Desktop and a WSL config file
LM StudioEngine and chatInstallerYesNot documented on its requirements pageNeeds a CPU with AVX2; 16 GB RAM and a 4 GB graphics card recommended, so the ASUS is below spec; it ran there in my 2024 test
AnythingLLMDocuments and chat surfaceDesktop app, or DockerOptional, built inOpenRouter supported: paste the key and the model list fills inMIT license; recommended for non-technical users in Jean Galea’s comparison
JanEngine and chatDesktop appYesOpenRouter supported under Settings, Model ProvidersOpen source (Apache 2.0 per Jean Galea)
GPT4AllSimple engine and chatDesktop appYesNot checkedSimplest option per Jean Galea, but no longer being updated; a baseline only

Protocol, on the ASUS under the Phase 2 load, for each tool:

  1. Install: download size, minutes to a working chat, number of steps, whether it needs admin rights, Docker or WSL, and disk used.
  2. Idle cost: memory the app uses with no model loaded.
  3. Same small model, same tasks: a 300-word email, a summary of a two-page PDF, and a 1,500-word first chapter from the control prompt. Record time to first word and words per minute.
  4. The OpenRouter bridge: can I add a key, pick a model and set a spending cap, and how many steps does it take?
  5. Where would a beginner get stuck? Note every error message and every moment that needs outside help.

Optional, and the strongest evidence for the letter: ask a non-technical friend to install the top two tools using only the official instructions, and write down where they get stuck.

Phase 4: OpenRouter and direct API models

Run the same control prompt through BookyAI’s OpenRouter and API connections, and measure what a good book costs in dollars instead of hardware.

Three tiers, chosen from OpenRouter’s current list when the phase starts, not from memory:

  • Cheap open-weight models: three or four of the largest open models at the lowest prices, including at least one 70B-class and one 120B-class model, the sizes my 4070 can’t run.
  • A free model (ID ending in :free). OpenRouter’s documented limit is 50 requests a day until you’ve bought $10 of credits, then 1,000. A BookyAI book takes more than 30 requests, so test whether a free-tier user can finish one book in a day.
  • Frontier references: one Claude, one ChatGPT and one Gemini Pro model, as the ceiling.

Rules: put a spending cap on every key (OpenRouter supports this per key) and record the actual cost from OpenRouter’s activity log, not an estimate. Measure the same things as every local run.

The numbers the open letter needs: cost per book, judge score per book, and the cheapest model that beats the best local model on the 4070.

What every run records, and the controls

New columns for the run matrix: platform, Ollama version, free memory at start (GB), load profile (clean or loaded), restarts, hands-on minutes, cost in dollars, second judge score.

Kept from the current method: words, length vs. target, repetition (bookdiff), highest single-chapter repetition, chapters 21-30 vs. 1-10, frame breaks, wall clock, tokens per second, BookyAI version, and model tag with its ID.

Controls:

  • Pin versions for a whole phase, and log every update in confounds_log.
  • Use a neutral project title on every run, and check each book for leaked labels before judging.
  • Judge blind: give judges a renamed file with any leaked labels replaced.
  • Use two judges from different labs. ChatGPT judging books written by OpenAI models is a known bias, so in Phase 4 pair it with a Gemini or Claude judge and use both scores. Run three trials for finalists.
  • For finalists, read 20 pages myself before believing any score.

Tooling to add: a seam check in bookdiff for passages repeated right after themselves, and a short script that counts failed requests in Ollama’s server.log.

Run it yourself: the community edition

Anyone can run this part on the computer they already have, using only free software, and open-source software where possible. That’s where it differs from my BookyAI tests, which use paid software. Teens are welcome, with a parent’s or guardian’s OK.

You need: a Windows, Mac or Linux computer with at least 8 GB of memory and about 10 GB of free disk space. No graphics card required.

  1. Describe your computer: laptop or desktop, roughly what year you got it, processor, memory (GB), graphics card and its memory (if any), operating system and free disk space.
  2. Install one free app: Ollama, Jan or AnythingLLM (all open source), or LM Studio (free, but not open source). Open WebUI works too if you’re comfortable with more setup. Note how long setup took and anything confusing.
  3. Download one model, sized to your memory. With 8 GB, try qwen3.5:2b (2.7 GB) or qwen3.5:4b (3.3 GB). With 16 GB, gemma4:e2b (4.6 GB) or gemma4:e4b (6.6 GB) too. With a graphics card of 8 GB or more, gemma4:e4b and larger. Sizes are Ollama’s download sizes; other apps may name models differently, so write down exactly what you used.
  4. Leave your computer as it normally is. Don’t close your usual programs. Note how many apps and browser tabs are open, and how much memory is free (Task Manager, Performance tab on Windows; Activity Monitor on a Mac).
  5. Run the three prompts below, each in a new chat. For each one, record: seconds until the first word appears, total time, whether it finished, and tokens per second if the app shows it.
  6. Send your results through the form [FORM LINK]. Paste the AI’s answers too if you’re willing.

The three prompts (copy them exactly):

A. Email: Write a polite email of about 150 words to a teacher asking for a three-day extension on an essay because of a family emergency. Include a subject line.

B. Summary: Summarize the notice below in three bullet points, then list one question a resident might still have.

Maplewood Branch Library will close for repairs from March 3 to March 21. During the closure, the book drop beside the front door stays open, and items due while the branch is closed will be renewed automatically. Holds placed for pickup at Maplewood will be sent to the Elm Street Branch, which will extend its hours to 8 p.m. on weekdays. The weekly homework help sessions will move to the Elm Street community room at the same times. Public computers will not be available at Maplewood, but laptops can be borrowed at Elm Street for use inside the building with a library card. The repairs include a new roof, a wheelchair-accessible restroom and faster internet throughout the building. Staff ask patrons to watch the library’s website for any change to the reopening date.

C. Story: Write the opening scene of a short story, about 800 words. A burnt-out freelance web designer launches a small website that pairs AI-generated art with daily affirmations, and the AI starts giving strangers advice that is impossibly specific. Third person, warm and grounded.

What happens to your results: they go into a public, read-only results sheet with names and emails removed. The form asks for no personal information, and contact details are optional. If you’re under 18, please ask a parent or guardian before installing anything, and leave your name out. If you’re under 13, have a parent send the results.

The form asks for: computer type and year, processor, memory, graphics card and its memory, operating system, the app and its version, the model exactly as named, time to install, free memory and open apps or tabs, and for each prompt the time to first word, total time, tokens per second, whether it finished, and the answer. It ends with “Anything confusing or broken?” and an optional email for follow-up.

Order of work and the posts it feeds

Each phase ends in a post, and the open letter comes last, built on all of them.

OrderWorkPost it feeds
1Publish the gemma4:e4b post“Yes, You Can Write a Book on an 8 GB Laptop. Bring Patience.”
2Phase 1: model sweep on the 4070The best small local model for long-form writing
3Phase 2: laptop finalists, clean vs. loadedFolded into posts 2 and 4
4Phase 3: platforms on the ASUSWhich free AI app works on a normal laptop (and an update to my 2024 Open WebUI guide)
5Phase 4: OpenRouter and API modelsWhat a good book costs: local vs. hosted
6Open letter to Stripe and OpenRouterMy site as the hub with the data; LinkedIn for the business case; Medium for the policy case

Target dates come once Phase 1’s first runs show how long a run really takes.

Open questions

  • Which second judge: Gemini or Claude?
  • Is the ASUS RAM soldered, or is there a slot for an upgrade?
  • Will BookyAI lengthen its 5-minute wait for local engines?
  • Can a free OpenRouter model finish a whole book inside 50 requests a day?
  • Does the Open WebUI desktop app install on Windows 11 Home with no Docker?
  • Find a source on the age and type of devices in lower-income homes (phones and computers) before stating it.
  • Is there a non-technical friend willing to test the installs?

Sources

Tagged: AI,personal growth
Categorized: Local AI Benchmarks, Reflections