Free big model API: Who can still prostitute for free, who can really fight
2026-07-30 True tune: I adjusted the APIs of more than a dozen large model models that can be used for free prostitution, and pinched the stopwatch to record today's usability, speed and pitfalls. Who can fight, who can use it but is slow, and who is disabled today? There are four traps for white prostitutes.
Today (July 30, 2026), I did something quite boring but useful: I adjusted the more than a dozen large model APIs in my hand that allowed free prostitution, and held a stopwatch to note their current usability, speed and pit.
With free big models, policies are changing very quickly. Most of the "Top Ten Free Models" lists on the Internet are from a few months ago, and you will miss them if you follow them. So this article does not talk about theory, but will give you a true picture of today: who can still prostitute for free, who can really beat, and who has been abolished. The free quota and availability will change at any time, subject to each official, but the methods and traps are common.
Let's put forward the conclusions first.
The first echelon is fast and free, suitable for being the main force or high-frequency calls. Cerebras 'gpt-oss-120b returned in 0.56 seconds today, with a free quota of 1 million tokens a day. This speed and magnitude are the most cost-effective for tasks that require frequent calls. Smart Spectrum's GLM-4-Flash is even more ruthless, 0.34 seconds, permanently free and uncapped. It is not the smartest, but it wins because it is fast, stable and always. I have always used it as the last fuse for the entire chain. There are also Groq, NVIDIA, and Gemini, all in about one second, and the amount is enough for daily use.
The second echelon, strong but slow, is suitable for places with high quality requirements but infrequent calls. Volcano's GLM-5.2, the access point for "Collaboration Reward" is free, and the daily amount is very large. However, today's actual measurement takes 7 seconds to return, and it is easy to read and timeout. Use it as a real-time event with users waiting nearby. card. Mistral Large's free quota of one billion tokens a month is very fragrant, and it will take 6.8 seconds today. GitHub's GPT-4.1 is of good quality, but it only gives it about fifty times a day, leaving it for low-frequency heavy work.
Then there are the few that rolled over today. ModelScope's DeepSeek-V4, I adjusted it to 429 twice in a row, and the current was limited. Not long ago, it was still working well 2,000 times a day. OpenRouter's free Llama, directly 404, has been removed from shelves, and its free model names are changed very frequently. There is also a batch that died completely in arrears: SiliconFlow, Alibaba Bailian, Baidu Qianfan, and Tencent Hunyuan. When transferred, either the balance is zero or the key is invalid. What's interesting is SambaNova. Last month, I remembered that it was dead in arrears (402). Today, it was resurrected and can be used again.
You see, this is the true state of the free model: what is available today may be current-limited tomorrow, and what died last month may be resurrected this month. Don't trust any list that lasts longer than a week.
For a real run, several pitfalls are worth mentioning individually, and they are all known after spending money or conducting process verification.
The first pit is also the most hidden one: the free volcano has a prerequisite. Its free credit is a "collaboration reward", and you must use the "authorized access point"(ID that starts with a string of EP) it gives you to adjust it to be counted as free. If you just fill in the model name and adjust it, it will charge you as token and deduct money once you adjust it. This rule is hidden in the background document, and nine out of ten people who pick it up for the first time will follow it.
I stepped on the second pit myself today. For models like gpt-oss that "think first and answer later", if you set max_tokens very small, such as only ten, it will spend all this amount on internal thinking, and the text returned to you will be empty. This happened when I tested Cerebras for the first time. I thought it was dead, so I enlarged max_tokens to 300 and adjusted it again, and a normal reply came out. With this kind of reasoning model, the token upper limit is too tight.
The third pit is psychological: don't regard free as stability. As I said before, SambaNova was resurrected, ModelScope was current-limited, and OpenRouter was changed. The GLM-4.7-Flash of Smart Spectrum took 46 seconds last month, and it only took 0.8 seconds today. The speed is like a roller coaster. The free quota is used by each family to recruit new ones and cut it at any time. So if you really use it to make something serious, you must string a fallback chain. When the main force hangs, it will automatically replace the next one. Don't bet your life on any one.
The last pitfall is a pitfall for spending money: Don't put a pay-per-token model into a pool that will be automatically and frequently called. Bean buns and DeepSeek officials will deduct money at a time. What's more troublesome is that once the account is in arrears, it will lock all models under your account, including those that are originally free. Free pool, only really free pool.
If you really want to build something with a free large model, my collocation is like this: high frequency, fast live, Cerebras or GLM-4-Flash at the head of the chain; quality, equal heavy live, volcano or Mistral; finally always pad a GLM-4-Flash bottom, because it does not top, almost do not hang. The key is not to use only one, free will hang at any time, more than a few layers, so that one day a limit, your whole thing will collapse.
Free large models can be white prostitutes, can do a lot of work, but it gives you a "quota", do not regard it as a "promise". Use it as something that will disappear at any time, and you will not be fooled by it.