Free LLM API Tiers in October 2026: What's Left and How I Chain Them
I run a handful of internal tools that call a language model a few hundred times a day: a changelog summarizer, a ticket classifier, a script that turns noisy logs into a readable incident timeline. None of them justify a monthly bill, so for the past year they have lived entirely on free LLM API tiers. That works, but only if you treat "free" as a set of quotas you have to manage, not a gift.
The lists that rank for this topic are mostly snapshots from spring. Since then, providers have been dropped, models have been retired and limits have moved. This post is what the landscape looks like on 6 October 2026, the catches I've had to design around, and the small fallback chain I use so one provider's daily cap doesn't take a tool down.
One scoping note before the details: every tier below is text-only, or close to it. When a project needs image or video generation I don't bother hunting for free quotas; I send those calls to Synexa, which runs models like FLUX Schnell behind a single predictions endpoint. Everything else in this post is about text.
Three kinds of "free"
Before comparing numbers, it helps to separate what providers mean by free, because the failure modes differ.
1. Permanent quota. A fixed number of requests or tokens per minute and per day that resets. Groq, OpenRouter's :free models, NVIDIA NIM and Google Gemini work this way. When you run out you get a 429 and wait.
2. Monthly credit allowance. A dollar amount that refills monthly. Mistral's free plan carries $10/month in API credits; Hugging Face gives free users $0.10/month of Inference Provider credit. When it's gone, it's gone until the month rolls over.
3. Anonymous or keyless access. No signup at all. OVHcloud AI Endpoints allows 2 requests per minute per IP per model without a key, Kilo Code's gateway serves its free pool at 200 requests per hour per IP, and LLM7.io lets anonymous callers reach its turbo models. Great for prototypes, fragile for anything you'd page someone over.
Trial credits that expire don't count, and I've left them out.
The free LLM API landscape as of October 2026
These figures come from the community-maintained awesome-free-llm-apis list, cross-checked against Groq's and OpenRouter's own rate-limit pages where I could. Every one of these endpoints is OpenAI SDK-compatible unless noted.
| Provider | Example free models | Free limit | The catch |
|---|---|---|---|
| Groq | openai/gpt-oss-120b, openai/gpt-oss-20b, qwen/qwen3.8-27b | 30 RPM, 1K RPD, 8K TPM, 200K TPD per model | Limits apply per organization, not per key |
| OpenRouter | nvidia/nemotron-3-super-120b-a12b:free, google/gemma-4-31b-it:free and others | 20 RPM, 50 RPD (1,000 RPD after $10 in credits) | Free providers may log prompts |
| NVIDIA NIM | openai/gpt-oss-20b, nvidia/nemotron-3-super-120b-a12b | 40 RPM, 10,000 RPD per model | Needs NVIDIA Developer Program membership |
| Google Gemini | Gemini 3.x and 2.5 Flash / Flash-Lite, 2.5 Pro | Google no longer publishes per-model free limits; check AI Studio | Free-tier prompts may be used to improve products (not in EEA/UK/CH) |
| Mistral | Mistral Medium 3.5, Small 4, Large 3, Codestral | $10/month in credits | Free-mode prompts may train models unless you opt out |
| Cloudflare Workers AI | @cf/meta/llama-3.3-70b-instruct-fp8-fast, @cf/openai/gpt-oss-120b | 10,000 Neurons/day, shared across all models | Not OpenAI-style; uses its own /ai/run URL |
| Cohere | Command A, Command R+, Aya Expanse 32B | 20 RPM, 1,000 calls/month | Trial key is non-commercial only |
| Z AI (Zhipu) | GLM-4.7-Flash, GLM-4.6V-Flash | 1 concurrent request | GLM-4.5-Flash retirement announced |
| ModelScope | Qwen3.5-35B-A3B, Qwen3.5-27B | 2,000 RPD total, up to 500 per model | Alibaba Cloud binding plus real-name verification |
| SiliconFlow | Qwen/Qwen3-8B | 1,000 RPM, 50,000 TPM | Real-name ID verification since May 2026 |
Compared with the March version of the same list, Cerebras, GitHub Models and Kluster AI no longer appear in it, and several newer entries (Aion Labs, Kilo Code, OVHcloud, ModelScope) do. Groq also shut down qwen/qwen3.6-27b on 14 September 2026 in favor of qwen/qwen3.8-27b. If you copied model IDs from an older article, check that they still resolve before you blame your own code.
The catches I actually design around
Daily caps hurt more than per-minute caps. OpenRouter's free models default to 50 requests per day per account until you've bought $10 of credits, at which point the ceiling becomes 1,000. Per-minute limits only slow you down; a daily cap stops you until midnight UTC. My rule: a provider with a low daily cap goes last in the chain, never first.
Know which header means what. Groq sends x-ratelimit-remaining-requests on every response, and its docs are explicit that this always refers to requests per day, while x-ratelimit-remaining-tokens refers to tokens per minute. retry-after only shows up on an actual 429. OpenRouter is the other way round: successful responses carry no rate-limit headers, so you query the key instead:
curl https://openrouter.ai/api/v1/key \
-H "Authorization: Bearer $OPENROUTER_API_KEY"
# look at data.free_model_daily_requests -> { used, limit, remaining }
Shared pools are easy to drain by accident. Cloudflare's 10,000 daily Neurons are shared across every Workers AI model on the account and reset at 00:00 UTC. Going over does not bill you; the request fails. A runaway embedding job can quietly starve your chat model. Groq's limits are also per organization, so two services sharing one org share one budget.
"Free" sometimes means "you are the training data." Google says free-tier prompts may be used to improve products, except for users in the EEA, Switzerland and the UK. Mistral's free mode may train on inputs unless you opt out. OpenRouter notes that free providers may log prompts. I keep anything containing customer data off these tiers entirely, and that one rule decides which tools can use them at all.
Regional and identity gates. SiliconFlow and ModelScope require real-name verification, which in practice means Chinese documents or a support ticket. Gemini's terms say that if you make an API client available to users in the EEA, Switzerland or the UK, you must use paid services. If you have users there, read that section before building on the free quota.
The SDK's own retries work against you. The OpenAI Python SDK retries 429s by default, sleeping between attempts. On a free tier that's exactly wrong when another provider has capacity right now. I set max_retries=0 and let my own chain decide where the next attempt goes.
A fallback chain that survives 429s
Because Groq, NVIDIA NIM and OpenRouter all speak the OpenAI Chat Completions format, one client class covers all three. The order reflects headroom: NVIDIA's 10,000 RPD first, Groq's 1,000 RPD second, OpenRouter's 50 RPD last as an emergency spare.
import os
from openai import OpenAI, RateLimitError, APIStatusError, APIConnectionError
# (name, base_url, env var holding the key, model id)
PROVIDERS = [
("nvidia", "https://integrate.api.nvidia.com/v1", "NVIDIA_API_KEY", "openai/gpt-oss-20b"),
("groq", "https://api.groq.com/openai/v1", "GROQ_API_KEY", "openai/gpt-oss-120b"),
("openrouter", "https://openrouter.ai/api/v1", "OPENROUTER_API_KEY",
"nvidia/nemotron-3-super-120b-a12b:free"),
]
# max_retries=0: fail fast and move to the next provider instead of sleeping
CLIENTS = [
(name, OpenAI(base_url=url, api_key=os.environ[env], max_retries=0, timeout=60), model)
for name, url, env, model in PROVIDERS
if os.environ.get(env)
]
def chat(messages, **kwargs):
errors = []
for name, client, model in CLIENTS:
try:
resp = client.chat.completions.create(model=model, messages=messages, **kwargs)
return name, resp.choices[0].message.content
except RateLimitError:
errors.append(f"{name}: 429")
except APIStatusError as e: # 402 on OpenRouter means a negative balance
errors.append(f"{name}: {e.status_code}")
except APIConnectionError:
errors.append(f"{name}: connection error")
raise RuntimeError("every free tier refused: " + ", ".join(errors))
if __name__ == "__main__":
provider, text = chat(
[{"role": "user", "content": "Summarize: deploy failed, migration 042 timed out."}],
max_tokens=200,
)
print(f"[{provider}] {text}")
Two things I learned the hard way. First, return the provider name with every answer and log it; when output quality shifts, that log tells you whether a fallback happened. Second, don't treat every model in the chain as interchangeable. A 20B model and a 120B model will not give the same answers, so I only chain models I've checked on my own prompts, and I keep prompts plain enough that the weakest model in the chain still copes.
Which tier I'd pick for what
- Batch jobs and classifiers: NVIDIA NIM, for the daily headroom.
- Interactive tools where latency matters: Groq first, with the chain behind it.
- Trying many models quickly: OpenRouter's :free variants; one key, many models, and openrouter/free routes to whatever free model is available.
- Long-context or multimodal input: Gemini, after checking your quota in AI Studio and the data-use terms for your region.
- Zero-signup demos: OVHcloud's anonymous tier or Kilo Code's gateway, accepting that they can change without notice.
FAQ
Is there a completely free LLM API with no credit card?
Yes. Groq, OpenRouter's :free models, NVIDIA NIM, Gemini, Mistral's free mode and Cloudflare Workers AI all start without a card. OVHcloud's anonymous tier and Kilo Code's gateway don't even need a key.
Which free LLM API has the highest daily limit?
Among the OpenAI-compatible options, NVIDIA NIM lists 10,000 requests per day per model, well above Groq's 1,000 and OpenRouter's default 50. SiliconFlow's per-minute numbers are higher, but it needs ID verification.
Can I use a free LLM API in production?
For low-stakes internal tools, yes, with a fallback chain and no sensitive data. For anything customer-facing, read the terms: Cohere's trial key is non-commercial, and Gemini's terms require paid services for apps serving EEA, UK or Swiss users.
Why do I get 429 errors on OpenRouter free models so quickly?
Free variants are capped at 20 requests per minute and 50 per day until your account has bought at least $10 in credits. Call GET /api/v1/key and check free_model_daily_requests to see how many you have left.
Wrapping up
Free tiers in late 2026 are generous enough to run real internal tools, as long as you plan around daily caps, keep private data off them, and fail over instead of retrying in place. The landscape will keep shifting, so check model IDs against the provider's own docs every few months. And when a project grows past text, I keep the same one-endpoint habit for media and route image and video jobs through Synexa rather than juggling another set of quotas.
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🔥 ¡Modelos de IA GRATIS para PROGRAMAR! Conseguí sus API Keys Link del repo mnfst/awesome-free-llm-apis Si quieres apoyar al canal. Link para donación con Paypal: paypal.com Únete a este canal para acceder a sus beneficios: youtube.com REDES SOCIALES TikTok: tiktok.com Canal de YouTube: youtube.com Web: informaticadp.com.ar Facebook: facebook.com Instagram: instagram.com [ar] 🔥 نماذج ذكاء اصطناعي مجانية للبرمجة! احصل على مفاتيح الـ API الخاصة بها رابط المستودع: mnfst/awesome-free-llm-apis إذا كنت ترغب بدعم القناة، إليك رابط التبرع عبر باي بال: paypal.com انضم إلى هذه القناة للاستفادة من مزاياها: youtube.com وسائل التواصل الاجتماعي تيك توك: tiktok.com قناة يوتيوب: youtube.com الموقع الإلكتروني: informaticadp.com.ar فيسبوك: facebook.com إنستغرام: instagram.com [en-US] 🔥 FREE AI Models for CODING! Get Their API Keys Repo link: mnfst/awesome-free-llm-apis If you'd like to support the channel, here's a link to donate via PayPal: paypal.com Join this channel to access its benefits: youtube.com SOCIAL MEDIA TikTok: tiktok.com YouTube Channel: youtube.com Website: informaticadp.com.ar Facebook: facebook.com Instagram: instagram.com [pt-BR] 🔥 Modelos de IA GRÁTIS para PROGRAMAR! Consiga suas API Keys Link do repositório: mnfst/awesome-free-llm-apis Se você quiser apoiar o canal, aqui está um link para doar via PayPal: paypal.com Torne-se membro deste canal para acessar seus benefícios: youtube.com REDES SOCIAIS TikTok: tiktok.com Canal do YouTube: youtube.com Site: informaticadp.com.ar Facebook: facebook.com Instagram: instagram.com
Hey! 👋🔥 As promised, here's the GitHub project for free AI APIs! 🚀 Awesome Free LLM APIs 🔗 mnfst/awesome-free-llm-apis It’s a curated list of AI providers offering free API tiers, so you can experiment with different LLMs and build AI apps without immediately paying for expensive APIs. Hope this helps you build something awesome! 🧡 Follow @clawdyai for more free AI tools, GitHub gems, and tutorials. 🚀
Links VoiceStudio: debpalash/VoiceStudio Odysseus: odysseus-dev/odysseus Free LLM APIs: mnfst/awesome-free-llm-apis Vane: ItzCrazyKns/Vane InvokeAI: invoke-ai/InvokeAI ACE-Step: ace-step/ACE-Step OpenShorts: mutonby/openshorts Dyad: dyad-sh/dyad OpenManus: FoundationAgents/OpenManus Upscayl: upscayl/upscayl These are alternatives, not drop-in replacements. Some run fully locally, some still need API keys, and several need a capable GPU or Docker. Check each project’s own installation instructions and licence before you rely on it.
You can call Gemini, Mistral and Cohere models for free, no credit card needed 🆓 It's called awesome-free-llm-apis, a curated list of LLM APIs with a permanent free tier. For each provider it tells you the exact models, context length, max output, modality and rate limits, so you know what you get before you sign up. Some examples from the list: - ✨ 𝗚𝗼𝗼𝗴𝗹𝗲 𝗚𝗲𝗺𝗶𝗻𝗶 Free tier with 1M context models like Gemini 2.5 Pro and Flash, no credit card - 🇫🇷 𝗠𝗶𝘀𝘁𝗿𝗮𝗹 𝗔𝗜 Free mode on by default with $10/month in API credits - 𝗖𝗼𝗵𝗲𝗿𝗲 Free trial key, 1,000 API calls per month, no credit card - ☁️ 𝗜𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗽𝗿𝗼𝘃𝗶𝗱𝗲𝗿𝘀 A second section covers the services that host open models for free It even has a glossary so the rate-limit jargon (RPM, TPD, RPD) makes sense. 📊 The numbers: → ⭐ 9.9K+ stars and 1K+ forks → 👥 6 contributors → 🌍 Providers from the US, France, Canada, Israel and more 👨💻 Maintained by Sébastien Conejo, co-founder of Manifest. 🔗 Link to the repo 👉 mnfst/awesome-free-llm-apis -- 📬 P.S. We hand-pick the best GitHub repos and send them twice a week, 100% free → lnkd.in -- ♻️ Save this and share it with anyone building on LLMs on a budget! 🙌 #opensource #github #AI #LLM #API 🤝 Sponsored by CUFinder, the largest B2B signal data platform
Finding a usable free LLM API shouldn’t mean checking every provider one by one. Awesome Free LLM APIs is a curated GitHub list of LLM APIs with permanent free tiers for text inference. It helps you compare options faster by putting provider API-key pages, endpoints, model details, context windows, modalities, and rate limits into one scan-friendly reference. Key features: • Provider vs. inference split – separates APIs run by model makers from third-party hosts for open-weight models • Direct access links – each provider heading links to its API-key page • OpenAI SDK compatibility notes – flags that listed endpoints are compatible unless noted otherwise • Model comparison tables – shows context, maximum output, modality, and rate-limit details for listed models • Practical glossary – defines RPM, RPD, TPM, TPD, and RPS so quota labels are easier to interpret It’s open-source (CC0-1.0 license). 🔗 GitHub: mnfst/awesome-free-llm-apis ⸻ ♻️ Share this with your network if you found it useful or insightful. ✉️ If you’re into AI, ML, agents, and building real systems, join my newsletter (it’s free): dankornas.substack.com
🔗 GitHub: mnfst/awesome-free-llm-apis --- ✉️ If you’re into AI, ML, agents, and building real systems, join my newsletter (it’s free): dankornas.substack.com
When building, testing, and prototyping new AI applications or multi-agent workflows, managing the ongoing costs of model inference can often slow down the experimentation phase. Having access to reliable, cost-free development resources is essential for rapid iteration. This is where curated developer repositories like awesome-free-llm-apis become incredibly valuable. It serves as an open-source directory that aggregates free LLM APIs, developer tiers, and trial endpoints provided by various platforms, giving engineers the freedom to test different architectures without financial friction. From a practical perspective, having a centralized list of accessible APIs allows developers to benchmark models, test pipeline integrations, and validate agentic behaviors freely during the early stages of a project. However, convenience must always be balanced with proper governance and security. Even when leveraging free development APIs, it is vital to protect sensitive data, avoid exposing enterprise credentials, and adhere to established development standards. Smart tooling and accessible resources accelerate innovation, empowering developers to build and test faster. 🔗 GitHub Repository: mnfst/awesome-free-llm-apis #AIAgents #SoftwareEngineering #DeveloperTools #OpenSource #AIInfrastructure #API #DigitalTransformation #Innovation #Qatar #Bahrain
我只能说总结的挺全的。 mnfst/awesome-free-llm-apis
Awesome Free LLM APIs: LLM APIs with permanent free tiers for text inference (9k stars) What it does All text below is quoted directly from the project README. >LLM APIs with permanent free tiers for text inference. All endpoints are OpenAI SDK-compatible unless noted. Each link points to the provider's API key page. Provider APIs: APIs run by the companies that train or fine-tune the models themselves. Inference providers: Third-party platforms that host open-weight models from various sources. A sample of the list: - Aion Labs: Permanent free tier, no credit card required. 15 RPM, 20K tokens/day. Specialized for roleplay and storytelling. - Cohere: Free "Trial" API key, no credit card. 1,000 API calls/month. Non-commercial use only. - Google Gemini: Free tier, no credit card. Free-tier prompts may be used by Google to improve products. - Mistral AI: Free mode, enabled by default, no credit card required. $10/month in API credits, and free-mode prompts may be used to train Mistral models unless you opt out. - Groq: Free tier, no credit card. Ultra-fast LPU inference. - OpenRouter: 17 free models (marked with :free suffix). OpenAI SDK-compatible. Repository mnfst/awesome-free-llm-apis Repository stats |Metric|Value| |:-|:-| |Stars|9,410| |Forks|1,003| |Last release|None| |Languages|JavaScript 100%| |Contributors|6| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|Claude: 4| |AI co-authored commits|None| Main contributor |Field|Value| |:-|:-| |Name|Sébastien Conejo| |GitHub|@SebConejo| |Commits to this repo|28 (top contributor)| |Bio|Co-founder of @mnfst. Passionate about design, creativity, and emerging technologies.| |Company / Location|Manifest, Berkeley| |Website|manifest.build| |Followers|82| |Public repos|181| |On GitHub since|2015-03-30|
Free LLM API Tiers in October 2026: What's Left and How I Chain Them I run a handful of internal tools that call a language model a few hundred times a day: a changelog summarizer, a ticket classifier, a script that turns noisy logs into a readable incident timeline. None of them justify a monthly bill, so for the past year they have lived entirely on free LLM API tiers. That works, but only if you treat "free" as a set of quotas you have to manage, not a gift. The lists that rank for this topic are mostly snapshots from spring. Since then, providers have been dropped, models have been retired and limits have moved. This post is what the landscape looks like on 6 October 2026, the catches I've had to design around, and the small fallback chain I use so one provider's daily cap doesn't take a tool down. One scoping note before the details: every tier below is text-only, or close to it. When a project needs image or video generation I don't bother hunting for free quotas; I send those calls to Synexa, which runs models like FLUX Schnell behind a single predictions endpoint. Everything else in this post is about text. Three kinds of "free" Before comparing numbers, it helps to separate what providers mean by free, because the failure modes differ. 1. Permanent quota. A fixed number of requests or tokens per minute and per day that resets. Groq, OpenRouter's :free models, NVIDIA NIM and Google Gemini work this way. When you run out you get a 429 and wait. 2. Monthly credit allowance. A dollar amount that refills monthly. Mistral's free plan carries $10/month in API credits; Hugging Face gives free users $0.10/month of Inference Provider credit. When it's gone, it's gone until the month rolls over. 3. Anonymous or keyless access. No signup at all. OVHcloud AI Endpoints allows 2 requests per minute per IP per model without a key, Kilo Code's gateway serves its free pool at 200 requests per hour per IP, and LLM7.io lets anonymous callers reach its turbo models. Great for prototypes, fragile for anything you'd page someone over. Trial credits that expire don't count, and I've left them out. The free LLM API landscape as of October 2026 These figures come from the community-maintained awesome-free-llm-apis list, cross-checked against Groq's and OpenRouter's own rate-limit pages where I could. Every one of these endpoints is OpenAI SDK-compatible unless noted. | Provider | Example free models | Free limit | The catch | |---|---|---|---| | Groq | openai/gpt-oss-120b, openai/gpt-oss-20b, qwen/qwen3.8-27b | 30 RPM, 1K RPD, 8K TPM, 200K TPD per model | Limits apply per organization, not per key | | OpenRouter | nvidia/nemotron-3-super-120b-a12b:free, google/gemma-4-31b-it:free and others | 20 RPM, 50 RPD (1,000 RPD after $10 in credits) | Free providers may log prompts | | NVIDIA NIM | openai/gpt-oss-20b, nvidia/nemotron-3-super-120b-a12b | 40 RPM, 10,000 RPD per model | Needs NVIDIA Developer Program membership | | Google Gemini | Gemini 3.x and 2.5 Flash / Flash-Lite, 2.5 Pro | Google no longer publishes per-model free limits; check AI Studio | Free-tier prompts may be used to improve products (not in EEA/UK/CH) | | Mistral | Mistral Medium 3.5, Small 4, Large 3, Codestral | $10/month in credits | Free-mode prompts may train models unless you opt out | | Cloudflare Workers AI | @cf/meta/llama-3.3-70b-instruct-fp8-fast, @cf/openai/gpt-oss-120b | 10,000 Neurons/day, shared across all models | Not OpenAI-style; uses its own /ai/run URL | | Cohere | Command A, Command R+, Aya Expanse 32B | 20 RPM, 1,000 calls/month | Trial key is non-commercial only | | Z AI (Zhipu) | GLM-4.7-Flash, GLM-4.6V-Flash | 1 concurrent request | GLM-4.5-Flash retirement announced | | ModelScope | Qwen3.5-35B-A3B, Qwen3.5-27B | 2,000 RPD total, up to 500 per model | Alibaba Cloud binding plus real-name verification | | SiliconFlow | Qwen/Qwen3-8B | 1,000 RPM, 50,000 TPM | Real-name ID verification since May 2026 | Compared with the March version of the same list, Cerebras, GitHub Models and Kluster AI no longer appear in it, and several newer entries (Aion Labs, Kilo Code, OVHcloud, ModelScope) do. Groq also shut down qwen/qwen3.6-27b on 14 September 2026 in favor of qwen/qwen3.8-27b. If you copied model IDs from an older article, check that they still resolve before you blame your own code. The catches I actually design around Daily caps hurt more than per-minute caps. OpenRouter's free models default to 50 requests per day per account until you've bought $10 of credits, at which point the ceiling becomes 1,000. Per-minute limits only slow you down; a daily cap stops you until midnight UTC. My rule: a provider with a low daily cap goes last in the chain, never first. Know which header means what. Groq sends x-ratelimit-remaining-requests on every response, and its docs are explicit that this always refers to requests per day, while x-ratelimit-remaining-tokens refers to tokens per minute. retry-after only shows up on an actual 429. OpenRouter is the other way round: successful responses carry no rate-limit headers, so you query the key instead: curl https://openrouter.ai/api/v1/key \ -H "Authorization: Bearer $OPENROUTER_API_KEY" # look at data.free_model_daily_requests -> { used, limit, remaining } Shared pools are easy to drain by accident. Cloudflare's 10,000 daily Neurons are shared across every Workers AI model on the account and reset at 00:00 UTC. Going over does not bill you; the request fails. A runaway embedding job can quietly starve your chat model. Groq's limits are also per organization, so two services sharing one org share one budget. "Free" sometimes means "you are the training data." Google says free-tier prompts may be used to improve products, except for users in the EEA, Switzerland and the UK. Mistral's free mode may train on inputs unless you opt out. OpenRouter notes that free providers may log prompts. I keep anything containing customer data off these tiers entirely, and that one rule decides which tools can use them at all. Regional and identity gates. SiliconFlow and ModelScope require real-name verification, which in practice means Chinese documents or a support ticket. Gemini's terms say that if you make an API client available to users in the EEA, Switzerland or the UK, you must use paid services. If you have users there, read that section before building on the free quota. The SDK's own retries work against you. The OpenAI Python SDK retries 429s by default, sleeping between attempts. On a free tier that's exactly wrong when another provider has capacity right now. I set max_retries=0 and let my own chain decide where the next attempt goes. A fallback chain that survives 429s Because Groq, NVIDIA NIM and OpenRouter all speak the OpenAI Chat Completions format, one client class covers all three. The order reflects headroom: NVIDIA's 10,000 RPD first, Groq's 1,000 RPD second, OpenRouter's 50 RPD last as an emergency spare. import os from openai import OpenAI, RateLimitError, APIStatusError, APIConnectionError # (name, base_url, env var holding the key, model id) PROVIDERS = [ ("nvidia", "https://integrate.api.nvidia.com/v1", "NVIDIA_API_KEY", "openai/gpt-oss-20b"), ("groq", "https://api.groq.com/openai/v1", "GROQ_API_KEY", "openai/gpt-oss-120b"), ("openrouter", "https://openrouter.ai/api/v1", "OPENROUTER_API_KEY", "nvidia/nemotron-3-super-120b-a12b:free"), ] # max_retries=0: fail fast and move to the next provider instead of sleeping CLIENTS = [ (name, OpenAI(base_url=url, api_key=os.environ[env], max_retries=0, timeout=60), model) for name, url, env, model in PROVIDERS if os.environ.get(env) ] def chat(messages, **kwargs): errors = [] for name, client, model in CLIENTS: try: resp = client.chat.completions.create(model=model, messages=messages, **kwargs) return name, resp.choices[0].message.content except RateLimitError: errors.append(f"{name}: 429") except APIStatusError as e: # 402 on OpenRouter means a negative balance errors.append(f"{name}: {e.status_code}") except APIConnectionError: errors.append(f"{name}: connection error") raise RuntimeError("every free tier refused: " + ", ".join(errors)) if __name__ == "__main__": provider, text = chat( [{"role": "user", "content": "Summarize: deploy failed, migration 042 timed out."}], max_tokens=200, ) print(f"[{provider}] {text}") Two things I learned the hard way. First, return the provider name with every answer and log it; when output quality shifts, that log tells you whether a fallback happened. Second, don't treat every model in the chain as interchangeable. A 20B model and a 120B model will not give the same answers, so I only chain models I've checked on my own prompts, and I keep prompts plain enough that the weakest model in the chain still copes. Which tier I'd pick for what - Batch jobs and classifiers: NVIDIA NIM, for the daily headroom. - Interactive tools where latency matters: Groq first, with the chain behind it. - Trying many models quickly: OpenRouter's :free variants; one key, many models, and openrouter/free routes to whatever free model is available. - Long-context or multimodal input: Gemini, after checking your quota in AI Studio and the data-use terms for your region. - Zero-signup demos: OVHcloud's anonymous tier or Kilo Code's gateway, accepting that they can change without notice. FAQ Is there a completely free LLM API with no credit card? Yes. Groq, OpenRouter's :free models, NVIDIA NIM, Gemini, Mistral's free mode and Cloudflare Workers AI all start without a card. OVHcloud's anonymous tier and Kilo Code's gateway don't even need a key. Which free LLM API has the highest daily limit? Among the OpenAI-compatible options, NVIDIA NIM lists 10,000 requests per day per model, well above Groq's 1,000 and OpenRouter's default 50. SiliconFlow's per-minute numbers are higher, but it needs ID verification. Can I use a free LLM API in production? For low-stakes internal tools, yes, with a fallback chain and no sensitive data. For anything customer-facing, read the terms: Cohere's trial key is non-commercial, and Gemini's terms require paid services for apps serving EEA, UK or Swiss users. Why do I get 429 errors on OpenRouter free models so quickly? Free variants are capped at 20 requests per minute and 50 per day until your account has bought at least $10 in credits. Call GET /api/v1/key and check free_model_daily_requests to see how many you have left. Wrapping up Free tiers in late 2026 are generous enough to run real internal tools, as long as you plan around daily caps, keep private data off them, and fail over instead of retrying in place. The landscape will keep shifting, so check model IDs against the provider's own docs every few months. And when a project grows past text, I keep the same one-endpoint habit for media and route image and video jobs through Synexa rather than juggling another set of quotas.