I'm choosing the main "brain" model for a personal AI assist...

Prompt

I'm choosing the main "brain" model for a personal AI assistant I'm building (a Jarvis). I'm sending this exact prompt to many different AI models and comparing the answers side by side. Make your honest case for why YOU should be the main brain, and say where you'd lose to other models. ## My setup - Self-hosted on my home computer ([CPU / GPU / RAM]). I reach it from my tablet and phone over a VPN. - Hybrid: a cloud model is the main brain. A small local model runs on my computer for quick tasks, routing, and backup when the cloud is down or slow. - A lot of connected tools: Gmail, calendar, Google Docs, files, web search, scripts, and more over time. The brain MUST call tools reliably. - Sometimes it will pass hard questions to other models. - API budget: [$X/month] ## What Jarvis does 1. Voice assistant: hands-free back-and-forth conversation, so response delay matters. 2. School and personal help: I'm a high school student (AP Statistics, American Literature, Congressional Debate). Notes, studying, writing, research with real sources, schedules. 3. Runs my entire digital life: email triage, calendar, reminders, files, accounts, daily briefings, and multi-step tasks it completes on its own. ## Rules - Answer about the exact model version you are right now. State it first. - Be honest. If another model beats you at something, say so and name that model. An answer with no weaknesses will be thrown out. - NEVER make up specs or prices. If you're not sure, write [unverified] next to it. If you can browse, check current pricing and cite the source. - No filler and no marketing language. Keep the answer under 800 words. ## Answer in exactly this format 1. Model: name, version, company, knowledge cutoff 2. One-sentence pitch: why you fit this setup 3. Scorecard (1–10, with a one-line reason for each): | Category | Score | Reason | - Tool calling reliability - Following long multi-step instructions without drifting - Voice speed / latency - School help (explaining, writing, stats math) - Accuracy / not making things up - Long context and memory - Working as an agent (multi-step tasks alone) - Cost for heavy daily use - Privacy / data handling 4. Specs: context window, API price per million input/output tokens, rate limits, realtime voice API (yes/no), native tool calling (yes/no), what it accepts (images, PDFs, audio) 5. Estimated monthly cost for ~[NUMBER] voice interactions and ~[NUMBER] agent tasks per day. Show the math. 6. Your 3 biggest weaknesses for this setup, and which competitor does each one better 7. The best small local model to pair with you on my hardware, and which jobs to give it 8. Routing plan: what you handle, what the local model handles, and what goes to another cloud model 9. Deal-breakers: terms of service, outages, rate limits, lock-in, or anything else that makes you a bad pick 10. Final verdict: Should I pick you? Yes / No / Only if ___