LLMWise is a multi-model API gateway that automatically routes each prompt to the cheapest healthy model across 16+ providers — including OpenAI, Anthropic, Google, Meta, xAI, and DeepSeek — and shows the exact model and cost on every response.
What is LLMWise?
LLMWise is a smart routing platform that accepts one prompt via chat or API and returns an answer from the cheapest available model that fits your plan’s constraints. It runs as a cloud service with an OpenAI-compatible message format and supports REST, Python, and TypeScript SDKs. The product is built by LLMWise (no company name beyond the product is given on the site) and targets developers who want to avoid juggling multiple provider dashboards.
Key Features
- Auto routing — Send a prompt without picking a model; LLMWise selects the cheapest healthy model from a curated pool (e.g., Gemini Flash, Llama, Gemma for simple tasks; DeepSeek V3, Qwen for mid-tier; GPT-4, Claude for premium when needed on Teams plan).
- Transparent per-response cost — Every answer displays which model ran and what it cost in USD, so users can audit spending without guessing.
- Compare, Blend, Judge — Run the same prompt across multiple models side‑by‑side (Compare), combine outputs into one response (Blend), or let models evaluate each other (Judge). Available on Teams plan.
- Circuit-breaker failover — When a provider returns errors, Auto reroutes to backup models without manual intervention, keeping applications operational.
- Bring Your Own Keys (BYOK) — Route through your own provider contracts using Fernet-encrypted key storage; still get routing, failover, and traceability through LLMWise.
- Zero-retention mode — Enable per‑account so prompts and responses are never stored, logged, or used for training; TLS 1.3 encryption in transit and AES‑encrypted storage at rest.
- Developer SDKs — REST API available today; Python and TypeScript SDKs under active development (quickstart examples provided).
Who is it for?
- Individual developers who want to reduce LLM spend by routing cheap prompts to open‑source models while reserving premium models only for tasks that need them.
- Teams building AI‑powered products that need resilience across provider outages and transparent cost tracking per API call.
- Budget-conscious startups that want to avoid overpaying for GPT‑4 or Claude Sonnet on everyday requests, using the free tier (5 messages) to test before committing to a paid plan.
What can you do with LLMWise?
- Reduce LLM costs — The cost calculator on the site estimates 32% savings for a $2,000/month spend by routing 70% of requests to OSS models (~90% cheaper) and 20% to mid‑tier (~60% cheaper).
- Compare models without switching apps — Use the Compare tool to see GPT‑4, Claude, Gemini, and DeepSeek answers side‑by‑side for the same prompt, then pick the best.
- Failover automatically — If a provider like Anthropic is down, Auto reroutes to a backup model so your app keeps running without manual reconfiguration.
How does LLMWise work?
- User enters a single prompt (via chat or API) and chooses Auto or a specific model (on Teams plan).
- Auto routing picks the cheapest healthy model from the plan’s pool — for Starter that’s a “Curated Auto pool” of open‑source models; for Teams it adds premium manual selection.
- The response shows the model name and cost in USD, then the next prompt repeats the selection.
Pricing
Free: 5 messages total, Auto only, 8K max context, 4K max output.
Starter: $29/month – 10M tokens, Auto lane, 128K context, 16K output, no manual premium models.
Teams: $99/month – 40M tokens, Auto + premium manual (GPT, Claude, Gemini Pro), 200K context, 32K output, includes Compare/Blend/Judge.
Enterprise: Custom limits, team billing, SLAs – contact sales.
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