Tokenstead - Find AI Models for Your Hardware
●LIVE<br>34 MODELS<br>56 HARDWARE<br>22 ADOPTERS TRACKED<br>38 UNIFIED-MEM DEVICES<br>HOMESTEAD YOUR AI
◆ Homestead your AI
Find the right model for your hardware
Run AI on hardware you own, so no vendor or government order can switch off the model you depend on. Pick your rig and see which open models fit - with honest speed estimates, cloud-pricing comparisons, and a source-cited tracker of who's running what.
01 - Select your hardware
click to compare
AMD Ryzen AI Halo 128GB
128GB UNIFIED
Framework Desktop 128GB
128GB UNIFIED
GMKtec EVO-X2 128GB
128GB UNIFIED
Mac Mini M4 16GB
16GB UNIFIED
Mac Mini M4 Pro 24GB
24GB UNIFIED
Mac Mini M4 Pro 48GB
48GB UNIFIED
Mac Studio M4 Max 36GB
36GB UNIFIED
Mac Studio M4 Max 64GB
64GB UNIFIED
Mac Studio M4 Max 96GB
96GB UNIFIED
or enter custom specs
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Unified (Mac/Jetson)<br>VRAM (GPU card)<br>System RAM
02 - Save your rig (free)
Sign in with GitHub to save your hardware. New here? We'll guide you through picking your rig - Mac, multi-GPU (up to 8x), or custom specs - then show you exactly which models you can run locally.
Sign in with GitHub - free
Top models by quality
Browse all models
01
DeepSeek V4 Pro<br>MoE
1600.0B params - 1000k ctx
89<br>GENERAL
02
GLM 5.2<br>MoE
744.0B params - 1000k ctx
88<br>GENERAL
03
Qwen3.6 35B A3B<br>MoE
35.0B params - 262k ctx
87<br>GENERAL
04
DeepSeek V3 0324<br>MoE
671.0B params - 128k ctx
87<br>GENERAL
05
DeepSeek V4 Flash<br>MoE
284.0B params - 1000k ctx
86<br>GENERAL
06
LongCat 2.0<br>MoE
1600.0B params - 1000k ctx
86<br>GENERAL
Who's running what
See all 22 →
Microsoft<br>runs<br>MAI<br>reported<br>Microsoft
Bloomberg: Microsoft replacing OpenAI/Anthropic models with in-house MAI models in Excel and Outlook to cut inference spend; a tuned MAI variant claims GPT-5.4 parity at up to 10x efficiency. Proprietary (not open-weight), but the same frontier-API cost pressure.
Smartly<br>runs<br>Llama 3.1 8B<br>confirmed<br>Meta
Self-hosted Llama 3.1 8B on Kubernetes automates support-ticket creation and resolution drafts for the ad-tech platform; 80% less time to create tickets.
Caisse des Depots<br>runs<br>Mistral Medium 3.5<br>confirmed<br>Mistral AI
Mistral Medium 3.5 (128B) for up to 100k French public-sector agents under a 4-year, EUR 140M framework; on-prem SecNumCloud option for sovereignty.
Capgemini<br>runs<br>Codestral<br>confirmed<br>Mistral AI
Self-hosted Codestral in its RAISE/SovBox coding assistant for regulated aerospace, defense and public-sector clients; code-completion accuracy 50% -> 90%.
SAP<br>runs<br>Codestral<br>confirmed<br>Mistral AI
Self-hosted, 100% European Codestral powers multilingual SBB rail support bots (1k -> 30k employees, 80% fewer repetitive queries) and an accounting accruals agent.
Statuses:<br>confirmed official source<br>reported credible third-party, not officially confirmed<br>testing evaluating, not deployed.
Curated and source-cited, not a scraper. Built a rig worth sharing?<br>Browse shared builds →.
34
Models tracked
56
Hardware configs
22
Adopters tracked