# LLMTest

> LLMTest is an AI proxy for solo devs and indie hackers. Route your LLM calls through our OpenAI-compatible endpoint to get cost tracking, automatic fallbacks, JSON recovery, and autopilot prompt optimization across 340+ models.

LLMTest helps you cut LLM API costs without breaking your prompts. You write a rough prompt and ship. Every week we run shorter and cheaper variants against your real traffic. Wins that clear every safety gate go live. One click reverts anything.

## Core pages

- [Homepage](https://llmtest.io/): product overview and pricing
- [Models](https://llmtest.io/models): directory of 340+ LLMs with prices and context windows, updated daily
- [Quickstart](https://llmtest.io/docs/quickstart): get an API key and make the first call in under a minute
- [Proxy / API Gateway](https://llmtest.io/docs/proxy): OpenAI-compatible endpoint documentation
- [MCP Setup](https://llmtest.io/docs/mcp-setup): connect LLMTest to Claude Code, Cursor, Windsurf
- [Benchmarks](https://llmtest.io/docs/benchmarks): how LLMTest benchmarks and judges models
- [Autopilot](https://llmtest.io/docs/benchmarks): weekly auto-optimization with safety gates

## API

- OpenAI-compatible endpoint: `https://llmtest.io/v1/chat/completions`
- Sitemap: https://llmtest.io/sitemap.xml
- Blog RSS: https://llmtest.io/blog/rss.xml

## Blog

- [How to cache LLM API calls in Node.js 2026: Redis and break-even math](https://llmtest.io/blog/llm-api-response-caching-redis-nodejs-2026): Redis exact-match caching cuts LLM API spend at scale. Working Node.js middleware, 30-minute TTL trade-off, and when semantic search is worth the overhead.
- [What is an AI agent? Tool loops, stalls, and 3 prod decisions](https://llmtest.io/blog/what-is-an-ai-agent): An AI agent is an LLM in a tool-calling loop. How loops work, why they stall or run away, and the 3 architecture decisions that matter in production.
- [How to add per-user LLM cost guardrails in Node.js in 2026](https://llmtest.io/blog/per-user-llm-cost-guardrails-nodejs-2026): Add per-user LLM budget caps with Redis: soft warnings at 80%, hard stops at 100%, and automatic model downgrade. Full Node.js middleware under 60 lines.
- [LLM fine-tuning cost in 2026: $3 to $30 self-hosted, break-even math](https://llmtest.io/blog/llm-fine-tuning-cost-2026): Fine-tuning LLMs in 2026 costs $3-$30 in GPU time for open-weight models, or a 50% inference premium on GPT-4.1. Break-even math across three real scenarios.
- [How to build a RAG API in Node.js 2026: pgvector and cited answers](https://llmtest.io/blog/rag-api-nodejs-pgvector-2026): Build a production RAG API in Node.js using pgvector: text ingestion, chunked embeddings, vector search, and source-cited answers in under 80 lines.
- [LLM hallucinations explained: causes, types, production fixes](https://llmtest.io/blog/llm-hallucinations-explained): Why LLMs hallucinate, the three error types, prompting patterns that reduce them, and the one production eval that catches failures before your users see them.
- [JSON mode explained: when schema enforcement beats prompting](https://llmtest.io/blog/json-mode-explained): JSON mode vs structured output: how constrained decoding works, when 3% failure rates become a real cost, and which enforcement approach your pipeline needs.
- [How to add context management to a Node.js chat API in 2026](https://llmtest.io/blog/llm-context-management-nodejs-chat-api-2026): Add token counting, sliding window, and summarization compaction to a Node.js chat route to keep conversations coherent without blowing the context budget.
- [LLM conversation costs in production 2026: $50/day without compaction](https://llmtest.io/blog/llm-conversation-context-costs-2026): Per-session cost math for 1,000 daily LLM chat sessions at three model tiers. Why stateless APIs compound costs and when sliding-window compaction pays off.
- [Best LLMs for unit test generation in 2026: coverage and cost](https://llmtest.io/blog/best-llms-unit-test-generation-2026): Five LLMs ranked on unit test quality, edge case coverage, and cost per 1,000 tests in 2026. Claude Haiku 4.5 is the value pick for solo devs.
- [Best LLMs for business email writing in 2026: Claude leads](https://llmtest.io/blog/best-llms-business-email-writing-2026): Best LLMs for business email writing in 2026: ranked by tone control, length discipline, and per-email API cost for solopreneurs.
- [How to queue LLM API calls in Node.js: BullMQ patterns](https://llmtest.io/blog/background-llm-jobs-bullmq-nodejs-2026): BullMQ turns long-running LLM API calls into background jobs with live progress events, stall detection, and dead-letter recovery in Node.js in 2026.
- [Cheapest LLMs for function calling in 2026: ranked by reliability](https://llmtest.io/blog/cheapest-llms-function-calling-2026): GPT-4o-mini, Gemini 2.5 Flash, DeepSeek V4-Flash, and Haiku 4.5 ranked on schema errors, retry costs, and multi-turn reliability for function calling in 2026.
- [LLM batch API cost in 2026: OpenAI vs Anthropic vs Google](https://llmtest.io/blog/llm-batch-api-cost-2026): Batch APIs from OpenAI, Anthropic, and Google give 50% off for async workloads. Here's the break-even math for three real use cases in 2026.
- [Best LLMs for multilingual support in 2026: 5 languages tested](https://llmtest.io/blog/best-llms-multilingual-support-2026): The best LLMs for multilingual apps in 2026: how frontier and budget models handle French, German, Japanese, and Arabic, with the token-cost math.