models.do
One API for 50+ AI Models
Access GPT-4, Claude Sonnet, Gemini Pro, Llama, and other models through a unified interface with intelligent routing and automatic fallbacks. Switch providers instantly with multi-provider redundancy.
import { Models } from 'models.do' // Intelligent routing selects best model per taskon.User.submits.Content($ => { const result = await Models.complete({ task: $.task, // classify, summarize, generate, analyze input: $.text, routing: 'auto' // GPT-4 → Claude → Gemini → Llama fallback }) return result}) // Cost-optimize: cheap models for simple tasks, smart for complexModels.analyze.with.CheapestModel({ text }) // Llama/Gemini FlashModels.reason.with.SmartestModel({ problem }) // GPT-4/Claude Opus
One of 48 primitives
models.do sits in Insight: measure, test and trace. Every .do shares one grammar, Business-as-Code, and one SDK.
Data
Records, vocabulary and search
Insight
Measure, test and trace
- Analytics
- Experiments
- Evals
- Benchmarks
- Trace
- Models
Frequently asked questions
OpenAI (GPT-4, GPT-4 Turbo, GPT-3.5 Turbo), Anthropic (Claude 3.5 Sonnet, Claude 3 Opus, Claude 3 Haiku), Google (Gemini Pro 1.5, Gemini Flash), Meta (Llama 3 8B/70B), Mistral (Mixtral 8x7B, Mistral Large), Cohere (Command R+), and 40+ other models via OpenAI-compatible endpoints. Add custom models by providing API endpoint and authentication. All models accessible through identical API—switch by changing one parameter.
Models.do analyzes task type (classification vs generation vs reasoning), input length (long context → Gemini/Claude), required speed (<500ms → fast models like GPT-3.5), output format (structured JSON → models good at tool use), cost constraints (budget limits), and historical performance. Machine learning optimizes routing based on your usage patterns. Override with custom routing rules. Save 40-60% on costs vs always using GPT-4 while maintaining quality.
Automatic failover to backup models in <200ms. Default chain: GPT-4 → Claude → Gemini → Llama. Configure custom chains per use case or globally. Models.do tracks provider uptime in real-time and routes around outages automatically. 99.99% uptime SLA backed by multi-provider redundancy. We've maintained 100% uptime since launch by failing over during provider incidents.
Yes. Split traffic between models (e.g., 50% GPT-4, 50% Claude) with automatic quality tracking (accuracy, latency, cost, user satisfaction). Define success metrics and statistical significance thresholds. Automatic winner selection promotes best performer. Gradual rollouts (10% → 50% → 100%) minimize risk. Test prompts, temperatures, and system instructions too. Full experimentation dashboard shows real-time results.
Intelligent routing uses cheapest adequate model (Llama/Gemini Flash for simple tasks, GPT-4 for complex reasoning). Automatic prompt compression reduces tokens by 30-50%. Semantic response caching avoids redundant API calls—identical prompts return cached results. Batch processing combines multiple requests. Per-model cost tracking with budget alerts and limits. Typical savings: 50-70% vs naive GPT-4-only usage. ROI calculator shows cost savings per use case.