Not all AI models write the same way. Ask GPT-4o to fix a typo and it might rewrite your entire paragraph. Ask a small local model to translate a business email and you'll get something that sounds like a textbook from 2004. The model you choose changes what you get back, sometimes more than the prompt itself does.
WindowSill lets you bring your own API key from OpenAI, Anthropic, Google, Mistral, xAI, OpenRouter, or run models locally through Ollama, LM Studio, and Azure AI Foundry. That flexibility is the point. But it also means you need to pick the right model for the job, and "right" depends on what kind of writing you're doing.
This guide breaks down which models work best for specific writing tasks: grammar correction, tone adjustment, translation, rewriting, and more.
Why the Model Matters More Than You Think
Most AI writing tools pick a model for you. You don't get a choice. That works fine until you notice the tool keeps making your casual Slack messages sound like corporate memos, or your translated emails lose every bit of nuance.
Different models have different strengths because they were trained on different data, with different priorities. Some are optimized for following instructions precisely (great for grammar fixes where you want minimal changes). Others are more creative and opinionated (great for rewriting, not great when you want your original voice preserved).
Here's a quick mental model: think of AI providers the way you'd think of different editors. One is meticulous about grammar but heavy-handed with style. Another has a light touch but misses some errors. A third is brilliant with foreign languages but expensive by the hour. You'd pick a different one depending on the job.
The Providers WindowSill Supports
Before comparing specific tasks, here's what you can connect to WindowSill with your own API key:
| Provider | Type | Example Models | API Key Source |
|---|---|---|---|
| OpenAI | Cloud | GPT-4o, GPT-4o mini, o3-mini | platform.openai.com |
| Anthropic | Cloud | Claude Sonnet 4, Claude Haiku | console.anthropic.com |
| Cloud | Gemini 2.5 Pro, Gemini 2.5 Flash | aistudio.google.com | |
| Mistral | Cloud | Mistral Large, Mistral Small | console.mistral.ai |
| xAI | Cloud | Grok | console.x.ai |
| OpenRouter | Cloud | Access to 200+ models from many providers | openrouter.ai |
| Ollama | Local | Deepseek R1, Gemma 4, Qwen 3.5 | Free, runs on your machine |
| LM Studio | Local | Gemma 4, Qwen 3.5, Mistral Small, Phi 4 Mini | Free, runs on your machine |
| Azure AI Foundry | Local | Microsoft Phi, select models | Free, runs on your machine |
You can also point WindowSill at any OpenAI-compatible API endpoint through the custom endpoint option. That covers self-hosted setups, corporate proxies, and smaller providers.
Best Models for Grammar and Spell Checking
Grammar checking sounds simple, but it's where model choice matters most. The ideal grammar model does two things: catches real errors and leaves everything else alone. That second part is harder than it sounds.
Top pick: GPT-4.1 nano or Gemini 2.5 Flash
Smaller, faster models tend to do better here than large ones. Why? Large models are more likely to "improve" text that didn't need improving. You asked for a spell check, not a rewrite. GPT-4.1 nano and Gemini Flash are fast, cheap (fractions of a cent per request), and good at following the "only fix errors" instruction.
Runner up: Claude Haiku
Anthropic's smallest model is also solid for grammar. It tends to be slightly more conservative than GPT-4.1 nano, meaning it's less likely to change your phrasing. If you find GPT models too eager to rewrite, try Haiku.
Avoid for grammar: Large reasoning models
Models like OpenAI o3, Claude Opus, or Gemini Pro are overkill for catching typos. They're slower, cost more per request, and sometimes overthink simple corrections. Save them for tasks that need real reasoning.
Local option: Phi-4 or Llama 3 8B
If you're running Ollama or LM Studio, Phi-4 handles English grammar surprisingly well for its size. Llama 3 8B is another good choice. Just don't expect local models to catch subtle punctuation issues in non-English text.
Best Models for Tone Adjustment
WindowSill has nine built-in tone presets: Professional, Friendly, Casual, Straightforward, Confident, Enthusiastic, Inspirational, Urgent, and Punchy. Tone adjustment is where the bigger models shine, because matching a specific voice requires understanding context and nuance.
Top pick: Claude Sonnet 4
Anthropic's models have a strong reputation for following nuanced style instructions. When you ask Claude to make something "friendly but not informal," it gets the balance right more often than other models. It's also good at preserving meaning while shifting register, the kind of thing that matters when you're adjusting a client email from "too blunt" to "assertive but polite."
Runner up: GPT-5
OpenAI's flagship is also strong for tone work. It handles the Professional and Confident presets particularly well. Where it sometimes stumbles is the Casual preset, where it can sound like a brand trying too hard to be relatable. Your mileage may vary.
Budget option: Gemini 2.5 Flash or GPT-5 nano
These handle common tone shifts (Professional, Friendly) well enough for quick messages. They struggle more with subtle presets like Punchy or Inspirational, where the output can feel generic.
Local option: Llama 3 70B (if you have the hardware)
Running a 70B-parameter model locally requires 40+ GB of RAM or a beefy GPU. But if you've got the hardware, Llama 3 70B handles tone adjustment surprisingly well. Smaller local models (8B and below) tend to flatten tone differences.
Best Models for Translation
Translation is the task where model choice has the biggest impact on quality. The gap between a good translation model and a mediocre one is the difference between "reads like a native speaker wrote it" and "technically correct but clearly machine-translated."
Top pick: GPT-5 or Claude Sonnet 4
Both handle major languages (Spanish, French, German, Chinese, Japanese, Korean) very well. GPT-5 edges ahead slightly on Asian languages based on public benchmarks, while Claude tends to produce more natural-sounding European language translations. For most users, either is excellent.
Best for many languages: Gemini Pro
Google's model supports over 100 languages and is particularly strong on languages that other models underserve (Turkish, Vietnamese, Thai, Arabic, Hindi). If you regularly translate to or from less common languages, Gemini is worth testing.
Budget translation: Mistral Large
Mistral was founded in Paris, and their models are particularly strong on French and other European languages. If your translation needs are mostly English to/from European languages, Mistral Large offers good quality at a lower price point than GPT-5 or Claude.
Local option: Caution
Translation quality drops off fast with smaller models. An 8B local model can handle basic Spanish or French, but anything involving Japanese, Arabic, or languages with complex grammar systems won't be reliable. If translation quality matters to you, use a cloud model.
WindowSill supports over 35 languages for translation, and the quality you get depends entirely on which model is behind it.
Best Models for Rewriting and Improving Text
The "Improve Text," "Lengthen," "Shorten," "Humanize," and "Simplify Language" actions all fall into this category. Rewriting is where large models justify their cost, because good rewriting requires understanding intent, not just syntax.
Top pick: Claude Sonnet 4
Claude models are consistently good at preserving your original meaning while improving clarity. The "Humanize" action in particular works well with Claude, because it tends to produce writing that sounds less stiff without swinging to the other extreme of forced casualness.
Runner up: GPT-5
Strong for the "Shorten" and "Simplify Language" actions. GPT-5 is good at cutting fluff, which makes it a solid pick when you want tighter writing. It can be slightly more aggressive about changing structure compared to Claude, so expect more dramatic rewrites.
For creative rewriting: Gemini Pro
If you want a rewrite that takes creative liberties, like turning a bullet list into flowing prose, Gemini's larger model can surprise you. It's also good at the "Lengthen" action, where other models sometimes pad text with filler.
Local option: Llama 3 8B for light editing
Can handle basic simplification and shortening for English text. Not ideal for heavy rewriting or the more creative actions.
Cost Comparison: What You'll Actually Pay
Since WindowSill Lifetime license uses your own API key, you pay the provider directly. Here's what typical writing tasks cost as of April 2026 (prices are approximate per-request for a typical 200-word text block):
| Model | Grammar Check | Tone Adjust | Translation | Full Rewrite |
|---|---|---|---|---|
| GPT-5 nano | ~$0.001 | ~$0.001 | ~$0.001 | ~$0.002 |
| GPT-5 | ~$0.01 | ~$0.01 | ~$0.01 | ~$0.02 |
| Claude Haiku | ~$0.001 | ~$0.001 | ~$0.001 | ~$0.002 |
| Claude Sonnet 4 | ~$0.01 | ~$0.01 | ~$0.01 | ~$0.02 |
| Gemini 2.5 Flash | ~$0.001 | ~$0.001 | ~$0.001 | ~$0.001 |
| Gemini Pro | ~$0.01 | ~$0.01 | ~$0.01 | ~$0.02 |
| Mistral Large | ~$0.006 | ~$0.006 | ~$0.006 | ~$0.01 |
| Ollama (local) | Free | Free | Free | Free |
A few things to note. The nano/flash models are roughly 10x cheaper than their bigger siblings. For grammar checks and quick tone shifts, that's an easy win. Save the big models for translation and full rewrites where quality differences are noticeable. And if privacy matters more than quality, local models through Ollama cost nothing to run (besides electricity and your hardware).
My Recommendations: A Cheat Sheet
Here's what I'd pick for each task if I were setting up WindowSill fresh today:
| Task | Best Pick | Budget Pick | Local Pick |
|---|---|---|---|
| Spell check | GPT-5 nano | Gemini 2.5 Flash | Phi-4 |
| Grammar fix | GPT-5 nano | Claude Haiku | Llama 3 8B |
| Tone: Professional | Claude Sonnet 4 | GPT-4o mini | Llama 3 70B |
| Tone: Casual | Claude Sonnet 4 | Gemini 2.5 Flash | Llama 3 70B |
| Translation (European) | Claude Sonnet 4 | Mistral Large | Not recommended |
| Translation (Asian) | GPT-5 | Gemini 2.5 Flash | Not recommended |
| Translation (rare languages) | Gemini Pro | Gemini 2.5 Flash | Not recommended |
| Improve / rewrite | Claude Sonnet 4 | GPT-4o mini | Llama 3 8B |
| Shorten | GPT-5 mini | GPT-5 nano | Llama 3 8B |
| Summarize | GPT-5 mini | Gemini 2.5 Flash | Llama 3 8B |
You don't have to pick just one. WindowSill lets you configure multiple providers at once and choose which model to use per request. So you can keep GPT-4o mini for quick grammar fixes and switch to Claude Sonnet for tone adjustments, all without leaving whatever app you're working in.
How to Set Up Your Preferred Model in WindowSill
- Open WindowSill and go to Settings > AI Providers
- Pick your provider (OpenAI, Anthropic, Google, etc.)
- Paste your API key
- WindowSill will load the models available on your account
- Select your preferred default model
- Done. Every AI text action will now use that model
You can change models anytime, and WindowSill remembers your preferred model per provider. If you want to try a different model for a specific task, you can switch right from the AI text popup before running the action.
For local models via Ollama, LM Studio or Foundry Local, check out the full setup guide.
Frequently Asked Questions
Can I use different models for different tasks in WindowSill?
Yes. You can configure multiple AI providers simultaneously and switch between them. WindowSill doesn't lock you into one model. You pick which one to use each time you run an AI action, or set a default and change it whenever you want.
Are local models good enough for daily writing tasks?
For English grammar checking and basic rewriting, yes. Models like Phi-4 and Llama 3 8B handle those tasks well. For translation, tone nuance, or non-English text, cloud models still have a clear advantage. The tradeoff is speed and privacy (local) versus quality and language coverage (cloud).
How much does it cost to use AI models through WindowSill?
You pay your provider's standard API rates. For most people doing a few dozen grammar checks and rewrites per day, expect to spend under $1/month with a mini or flash model. Heavy translation use with large models might run $5-10/month.
Does OpenRouter let me access all models through a single key?
Roughly, yes. OpenRouter acts as a gateway to models from OpenAI, Anthropic, Google, Meta, and others through one API key with unified billing. It's a convenient option if you want to experiment with many models without creating separate accounts everywhere. WindowSill has built-in OpenRouter support.
The right model depends on what you write, how much you're willing to spend, and whether privacy matters for your use case. Start with a cheap model for grammar, a capable one for translation, and experiment from there. That's the whole point of bringing your own key: you're in control.