Free-Tier LLM Text Inference Providers

aillmapifree-tierinferenceresearch

Bottom line

As of May 2026, there is a strong ecosystem of legitimate AI providers offering free tiers for text inference. Google AI Studio provides the most generous sustained free access (1,500 requests/day on Gemini 2.5 Flash with 1M token context). Groq and Cerebras deliver the fastest inference on open-source models. But OpenAI no longer offers automatic free API credits to new accounts, and Anthropic has no free API tier at all. No free tier offers an SLA, and several providers-notably Google Gemini outside the EU-may use prompt data for model training, making free tiers unsuitable for sensitive or production workloads without careful evaluation.

Key findings

  • Finding: Google AI Studio is the clear leader in sustained free-tier generosity. It offers 1,500 requests per day, 1 million tokens per minute, and 1M token context windows on Gemini 2.5 Flash, with no credit card required. This is enough to run a small chatbot or content pipeline indefinitely. (Sources: TokenMix, PE Collective, free-llm.Com)
  • Finding: OpenAI and Anthropic are effectively inaccessible without payment for new developers. OpenAI discontinued automatic free trial credits for new API accounts in late 2025; users must now add a payment method. Anthropic has no free API tier, only occasional $5 promotional credits. (Sources: GitHub Community Discussion, PE Collective, Stochastic Sandbox)
  • Finding: Inference speed and throughput vary dramatically. Groq delivers 315 tokens/second on Llama 3.3 70B via custom LPU hardware, while Cerebras offers ~1,000 tokens/second and 60K tokens/minute on its wafer-scale chips. By contrast, Hugging Face serverless inference can have queue times of 30 seconds to several minutes. (Sources: TokenMix, PE Collective, Stochastic Sandbox)
  • Finding: Data privacy isn't guaranteed on free tiers. Google AI Studio's free tier may use prompts for product improvement and model training unless users are in the UK, Switzerland, EEA, or EU. The result is legal and compliance risks for client work or proprietary data. (Sources: BSWEN Blog, free-llm.Com, PE Collective)
  • Finding: "Stacking" multiple free tiers is a viable strategy for small projects. Combining Google AI Studio (1,500 req/day), Groq (~1,000 req/day), and Cerebras (~1,700 req/day) can yield ~3,500–5,000 requests/day at zero cost, enough for ~1,000–1,500 daily active users. (Sources: TokenMix, DEV Community)

Background

The landscape of free LLM API access has shifted significantly since 2023–2024. Early on, OpenAI provided $5–$18 in automatic free credits to every new account, making it the default starting point for developers. That changed in late 2025, when OpenAI stopped granting automatic free credits and began requiring a payment method for API access.

Around the same time, a wave of open-source model providers and inference startups began offering permanent free tiers to attract developers. These include Google (Gemini), Groq, Cerebras, Mistral, Cloudflare, and aggregators like OpenRouter. The emergence of the OpenAI-compatible API standard means most of these services can be swapped with a simple base_url change, dramatically lowering switching costs.

Current state

Permanent free tiers (no expiration, rate-limited):

  • Google AI Studio: 1,500 req/day, 1M tokens/min, 1M context. Best for general-purpose apps.
  • Groq: ~1,000 req/day on Llama 70B, 6K–30K tokens/min, 315 TPS. Best for latency-sensitive tasks.
  • Cerebras: ~1,700 req/day, 60K tokens/min, ~1,000 TPS. Best for high daily throughput.
  • OpenRouter: 20 req/min, 50–200 req/day, 11+ free models. Best for model comparison.
  • Mistral (La Plateforme): 1 req/sec, 500K tokens/min, 1B tokens/month. Requires phone verification and opt-in to data training.
  • Cloudflare Workers AI: 10,000 neurons/day free. Equivalent to roughly ~300 short requests/day on Llama 70B, or more on smaller models.
  • GitHub Models: Free for all GitHub accounts via PAT or Actions GITHUB_TOKEN. Includes GPT-4o, Llama, DeepSeek, Mistral. Rate limits are low (~150 req/day) and tied to Copilot subscription tier.
  • Cohere: 1,000 API calls/month (~33/day). Good for embeddings and RAG prototyping.
  • Hyperbolic: 60 req/min free on Basic tier, plus $1 promotional credit with phone verification.

Trial credit providers (one-time, then pay-as-you-go):

  • SambaNova: $5 credit (expires in 30 days).
  • DeepSeek: 5M free tokens on registration.
  • AI21 Labs: $10 credit, 3-month expiry.
  • Together AI: $1 credit.
  • Fireworks: $1 credit.
  • Baseten: $30 credit.
  • Modal: $5/month recurring credit.

No free tier:

  • OpenAI: No automatic free credits; payment method required.
  • Anthropic: No free tier; minimum $5 spend to access API.

Technical or implementation details

  • API compatibility: Nearly all free-tier providers support the OpenAI chat/completions API format. This includes Groq, OpenRouter, Cerebras, GitHub Models, LocalAI, Ollama, and many others. Developers can reuse the same client code by changing base_url and api_key.
  • Rate limit mechanics: Most providers use token-bucket algorithms that refill continuously. Limits are expressed in RPM (requests per minute), TPM (tokens per minute), RPD (requests per day), or TPD (tokens per day). Google enforces RPD on free tiers; Groq enforces both TPM and TPD.
  • Cloudflare "neurons": Cloudflare abstracts GPU compute into "neurons." 10,000 neurons/day are free. For example, Llama 3.1 70B input costs ~26,668 neurons per million tokens, so the free tier allows roughly ~375K input tokens per day on that model. Smaller models like Llama 3.2 1B cost ~2,457 neurons per million tokens, stretching the free allocation much further.
  • Context windows: Free tiers generally support the same context windows as paid tiers for a given model. Google Gemini Flash supports 1M tokens. Cerebras and Groq support standard model limits (e.G., 128K for Llama 3.3). GitHub Models' free tier caps out at standard limits, with paid enabling up to 128K on supported models.

Evidence, comparisons, and related context

  • Speed benchmarking: Groq's custom LPU hardware achieves 315 TPS on Llama 3.3 70B, while SambaNova reaches 294 TPS. Cerebras claims ~1,000 TPS. Traditional GPU-based providers (Google, OpenRouter) are slower but offer higher daily request quotas.
  • Prior work / local alternatives: For developers with privacy concerns or who need unlimited inference, local deployment via Ollama, vLLM, or LocalAI is a mature alternative. Ollama offers one-command setup and an OpenAI-compatible API. VLLM provides production-grade throughput with PagedAttention. LocalAI is a full multimodal drop-in replacement. Hardware requirement: ~16GB RAM runs 7B quantized models at 4–8 tokens/sec.
  • Ecosystem: Real-world free-tier use cases include customer-support chatbots, internal document Q&A (RAG), content summarization, translation, blog generation, and code help. These align well with the throughput limits of free tiers. More complex multi-agent workflows are generally beyond free-tier capacity.

Limitations and critiques

  • Zero SLA: No free tier offers an uptime guarantee, support commitment, or compensation for outages. (Source: PE Collective, Featherless.Ai)
  • Data privacy risks: Google AI Studio's free tier may train on prompts outside the EU/EEA. Mistral's free tier requires opting into data training. Hyperbolic and some others advertise zero data retention, but policies should be verified directly. (Sources: BSWEN Blog, free-llm.Com)
  • Rate limit volatility: Providers change limits without notice. Community-maintained lists (e.G., cheahjs/free-llm-api-resources) explicitly warn: "Please don't abuse these services, else we might lose them." (Source: GitHub)
  • Hidden costs: When moving from free to paid, costs can include cold-start latency, egress bandwidth. GPU idle time for reserved instances-adding 10–25% to headline per-token pricing. (Source: Featherless.Ai)
  • Trial credit confusion: Some providers marketed as "free" (SambaNova $5, Hyperbolic $1) are actually trial credits with expiration dates, not permanent free tiers.
  • Source bias: TokenMix and Featherless.Ai operate competing inference services, which may influence their emphasis on certain providers or pricing models.

Open questions

  • Does Google's current AI Studio Terms of Service still permit training on free-tier prompts as of May 2026, or has the policy shifted?
  • How frequently do providers silently reduce free-tier rate limits, and are there documented cases of access being revoked mid-project?
  • What is the precise real-world request capacity of Cloudflare's 10,000 neurons/day across the full model catalog, given per-model neuron costs vary by 100x?

Practical takeaways

  • Start with Google AI Studio if you want the easiest, most generous free tier for general text inference. No credit card is required.
  • Use Groq or Cerebras when response speed matters more than daily volume. Both are OpenAI-compatible and require no payment.
  • Stack providers to extend free capacity: route general chat to Google, speed-critical requests to Groq, and model comparisons to OpenRouter. A simple fallback chain in your code can triple effective daily quota.
  • Avoid free cloud tiers for sensitive data. If you handle client work, healthcare data, or proprietary code, run local models via Ollama or vLLM, or use paid tiers with explicit no-training policies.
  • Don't build production architecture around a single free tier. Free limits change, there is no SLA, and scaling past ~5,000 requests/day is cheaper in engineering time on a paid tier like DeepSeek V4 ($0.30/M tokens) than managing multiple free providers.

Sources used

Research completed following the x-research skill workflow. Data current as of May 2026. Verify rate limits directly with providers before building, as they change frequently.