awesome-free-llm-apis: List of Permanent Free LLM API (API Keys)

by mnfst · Codex Skill · ★ 12.2k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 55/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentsanthropicawesomeawesome-listgeminillmllm-routerllm-routingollamaopenai

Quick Facts

Stars12,174
Forks1,406
LanguageJavaScript
CategoryCodex Skill
LicenseCC0-1.0
Quality Score55/100
Open Issues4
Last Updated2026-11-04
Created2026-03-21
Platformsgemini, node
Est. Tokens~13k

About awesome-free-llm-apis

LLM APIs with permanent free tiers for text inference. Contents Provider APIs Inference providers Provider APIs APIs run by the companies that train or fine-tune the models themselves. Cohere 🇺🇸 - Command A, Command R+, Aya Expanse 32B +9 more. 20 RPM, 1K/mo. Google Gemini 🇺🇸 - Gemini 2.5 Pro, Flash, Flash-Lite +4 more. 5-15 RPM, 100-1K RPD.

Compatible Skills

These tools work well together with awesome-free-llm-apis for enhanced workflows:

  • NadirClaw — semantic(0.38)+complementary+rare_topics+similar_pop+shared_platform (58%)
  • claw-empire — semantic(0.19)+complementary+rare_topics+similar_pop+shared_platform (51%)
  • openclaw-a2a-gateway — semantic(0.26)+complementary+rare_topics+similar_pop (48%)
  • vllora — semantic(0.19)+complementary+rare_topics+similar_pop+shared_platform (46%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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