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<divclass="tokens-sub">Across 60 free-tier models on 11 providers. Mistral alone contributes ~1B; everything else is bonus.</div>
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<sectionid="about">
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<divclass="section-header">
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<divclass="section-eyebrow">About the project</div>
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<h2>A single interface for the free web</h2>
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</div>
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<divclass="about-layout">
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<divclass="about-story">
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<p>
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<strong>FreeLLMAPI</strong> is designed to solve a simple problem: AI companies offer generous free tiers, but managing dozens of separate API credentials, rate limits, and custom SDKs makes integration impractical.
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</p>
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<p>
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By consolidating Google Gemini, Groq, Cerebras, and 8 other providers under a single, unified endpoint, FreeLLMAPI lets you build against the free web as if it were a single, highly available frontier model.
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</p>
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<p>
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The proxy runs completely locally on your hardware. Keys are stored encrypted with AES-256-GCM, and requests are translated in-flight to matching provider schemas with near-zero latency overhead.
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</p>
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</div>
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<divclass="features-grid">
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<divclass="feature-card">
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<divclass="feature-title">
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<spanclass="feature-badge">⚡</span>
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Aggregated Quota
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</div>
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<pclass="feature-desc">Combines free monthly API allowances into a massive virtual pool of over 1 billion tokens, using whichever keys have remaining quota.</p>
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</div>
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<divclass="feature-card">
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<divclass="feature-title">
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<spanclass="feature-badge">🔌</span>
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OpenAI Drop-In
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</div>
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<pclass="feature-desc">Compatible with official OpenAI SDKs, LangChain, LlamaIndex, Cursor, and any chat UI. Just point your client library to the local endpoint.</p>
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</div>
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<divclass="feature-card">
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<divclass="feature-title">
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<spanclass="feature-badge">🛡️</span>
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Decrypted & Safe
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</div>
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<pclass="feature-desc">Provider keys are encrypted at-rest using AES-256-GCM in SQLite and decrypted in-memory only when dispatching upstream requests.</p>
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</div>
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<divclass="feature-card">
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<divclass="feature-title">
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<spanclass="feature-badge">🔄</span>
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Smart Failover
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</div>
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<pclass="feature-desc">If a provider yields a 429, 5xx, or times out, the router automatically fails over to the next best model in your priority chain.</p>
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