Models
The qwen-turbo/text-to-text model is a state of the art large language model developed by Alibaba Cloud. It belongs to the renowned Qwen family, specifically optimized for high speed and low latency performance. As a turbo variant, it provides a perfect balance between intelligence and cost efficiency, making it ideal …
The Seed 1.6 Flash API delivers sub-second latency and extreme throughput for real-time apps. This Doubao iteration handles 128k context windows with native function calling, offering a superior cost-to-performance ratio for global scale.
Gemini 2 Flash is Google's speed-optimized multimodal model. Featuring a 1-million-token context window and native real-time audio/video processing, it is designed for sub-second latency in agentic workflows and live conversational apps.
The doubao seed 1.6 flash api offers high-performance bilingual AI with a 128k context window. Optimized by ByteDance for low latency and cost-efficiency, it excels in Chinese-English tasks and complex function calling for enterprise workflows.
Doubao 1.5 AI is ByteDance’s flagship reasoning model. It offers GPT-4o-class performance with superior bilingual logic for English and Chinese, optimized for tool-use and complex agents at a fraction of the cost of western models.
Experience the next evolution of reasoning with deepseek-v3.2/text-to-text, now fully integrated into the GPT Proto ecosystem. This model represents a significant leap in Mixture-of-Experts (MoE) architecture, providing unmatched efficiency for complex problem-solving and creative synthesis. Whether you are automating …
The GPT 5 Nano API is OpenAI's fastest multimodal model, offering 128k context and native audio processing. Perfect for high-volume orchestration and real-time support, it delivers superior reasoning at just $0.05 per million input tokens.
The GPT 4.1 nano api delivers sub-second latency and high-throughput performance. Optimized for structured outputs and vision tasks, this gpt model provides a cost-effective alternative to larger LLMs without sacrificing technical reliability.
Grok-4-1-fast-non-reasoning is a fast and efficient AI language model designed primarily for high-speed content generation and automation. Part of the Grok family, this model emphasizes throughput and reliability over complex reasoning, making it ideal for large-scale workflows, batch processing, and scenarios where ra…
grok 4.1 represents the pinnacle of real-time intelligence, designed to handle complex reasoning tasks with unparalleled speed. By integrating grok 4.1 into your workflow via the GPTProto platform, you unlock advanced capabilities in natural language understanding and data synthesis. The grok 4.1 model excels in enviro…
ai grok 3 mini is a high-efficiency reasoning model from xAI. It excels at coding tasks and real-time information retrieval via X integration, offering low-latency performance for developers via GPTProto.com.
Access GPT-6 Luna on GPTProto for high-volume chat, classification and structured extraction. Run focused tasks with adjustable reasoning and a 1.05M-token context window. Check the live rate and test the model using your GPTProto API key.
The gpt 4o mini api is a high-performance small model from OpenAI. It offers 128k context, native vision support, and low latency for high-volume tasks. Ideal for cost-conscious devs needing GPT-4 level intelligence at a fraction of the price.
OpenAI's gpt 4o mini api delivers superior intelligence for high-volume tasks. With a 128k context window and multimodal support, this mini model excels in reasoning and structured data extraction while maintaining ultra-low latency and cost.
Access Z.ai’s first natively multimodal GLM-5 model through GPTProto. Send text, images, videos, or files, retain up to 1M tokens of context, and use one API key and shared balance across 200+ supported models.
Access Anthropic's Claude Haiku 5.5 through GPTProto for high-volume classification, extraction, routing, support, and subagent work. Test it with one key and a shared balance across available models.
DeepSeek V3 API delivers frontier-level intelligence with 671B parameters. Optimized for coding and math, this MoE model offers a 128k context window and GPT-4o performance at significantly lower costs through GPTProto.com.
qwen-plus/text-to-text is a sophisticated large language model developed by Alibaba Cloud, belonging to the renowned Qwen family. As a mid to high tier model, it strikes an optimal balance between reasoning capabilities and computational efficiency. Designed for complex text generation and understanding, qwen-plus/text…
Gemini 3.5 Flash is a high-throughput multimodal model from Google, featuring a 1M token context window and native audio/video reasoning. Built for speed and efficiency, it delivers elite performance for long-document QA and real-time analysis.
The gemini-3.1-flash-lite-preview represents a paradigm shift in generative AI, offering an expansive 1 million token context window optimized for speed and efficiency. Unlike traditional models restricted by narrow memory, gemini-3.1-flash-lite-preview allows developers to upload entire codebases, multi-hour videos, o…
No model matches these filters.
| Output | Stability | Action | ||||
|---|---|---|---|---|---|---|
 Qwen Turbo30% off official | — | |||||
 Doubao Seed 1.6 Flash (Build 250615)15% off official | — | |||||
 Gemini 2.0 Flash40% off official | — | |||||
Doubao Seed 1.6 (Build 250615)15% off official | — | |||||
Doubao 1.5 Pro 32K (Build 250115)15% off official | — | |||||
 DeepSeek v3.240% off official | 163.84K | |||||
 GPT 5 Nano30% off official | 400K | |||||
GPT 4.1 Nano30% off official | 1.05M | |||||
 Grok 4.1 Fast Non Reasoning40% off official | — | |||||
Grok 4.1 Fast Reasoning40% off official | — | |||||
Grok 3 Mini40% off official | — | |||||
GPT 6 Luna20% off official | 1.05M | |||||
GPT 4o Mini (Build 2024-07-18)30% off official | 128K | |||||
GPT 4o Mini30% off official | 128K | |||||
 GLM 5.3 Flash15% off official | 1.05M | |||||
 Claude Haiku 5.510% off official | 1M | |||||
DeepSeek v340% off official | — | |||||
Qwen Plus30% off official | 1M | |||||
Gemini 3.1 Flash Lite40% off official | 1.05M | |||||
Gemini 3.1 Flash Lite Preview40% off official | 1.05M |
Affordable LLM Models on GPTProto
Compare text models by output price, starting at $0.14 per 1M output tokens. Sort by estimated monthly cost to see which model fits your budget.
LLM API Cost Calculator
Enter your monthly token usage to compare what each model would cost. If you only know your per-request usage, multiply the average input and output by the number of requests you expect each month.
Video and agent workloads burn credits faster — the recommendation adjusts automatically as you switch scenario or usage level.
What Is a Cheap LLM API?
A cheap LLM API keeps the cost of your requests low enough to run your workload at scale. Look at input and output prices together, then check whether repeated prompt text qualifies for a lower cache-read rate. Qwen Turbo has the lowest output price in the table. Estimated monthly costs also include input charges. At 10M input and 2M output tokens with no cached input, Qwen Turbo costs about $0.63 per month.
Why Choose GPTProto for a Low-Cost LLM API?
See What You Save on the Same Model
Compare the same model and usage at GPTProto and at the provider’s standard paid rate. If you already know which model works for you, compare the two rates before deciding where to run it.
Use One Key and One Balance
Try a lower-cost model for routine calls and keep a stronger model for work that needs it. Use one GPTProto API key and a shared prepaid balance across supported models. For an existing OpenAI-compatible chat integration, start with the base URL, key, and model ID shown on the model page.
4 Ways to Reduce Your LLM API Costs
1. Use a budget model for repeatable tasks
Try a low-cost model for extraction, routing, or short replies. Send harder cases to a stronger model when your evaluation shows it makes a difference.
2. Send less text per request
Keep the instructions and retrieved context the model needs to answer. Summarize older chat turns where you can and ask for concise output where a short answer works.
3. Measure cache hits on repeated prompts
Reuse stable instructions when the model supports prompt caching. Check your billed cache reads and any write or storage fees before using the cache rate in a budget forecast.
4. Track cost per successful task
Divide the total cost of a test run by the number of tasks that passed your checks. Include retries and any billable reasoning tokens. This gives you a better basis for choosing a model than input price alone.
Frequently Asked Questions
01What is the cheapest LLM API on GPTProto in 2026?
Qwen Turbo has the lowest standard output price among the text models compared on this page at $0.14 per million output tokens. Doubao Seed 1.6 Flash comes next at $0.1821 per million output tokens.
02How much does one LLM API call cost?
A call with 1,000 input and 200 output tokens costs about $0.00016 on GPT-6 Luna at the listed GPTProto rates. For a monthly estimate, multiply each per-call token count by the number of calls you expect and enter the totals above.
03Is GPTProto cheaper than buying directly from the model provider?
It depends on the model and rate. For example, GPT-6 Luna’s standard input and output rates are 20% lower on GPTProto than OpenAI’s standard rates in this comparison. Check the exact model and tier, especially if you already use a provider’s batch or promotional pricing.
04What is the most cost-effective LLM for coding?
Start with a model that completes your typical edit and passes your tests. Compare the cost of accepted patches across models using the same tasks. Include retries, repository context, and any reasoning tokens in the total.
05Do I need to buy a separate API key for every model?
You can use one GPTProto API key and one prepaid balance across supported models. Create a key, choose a model, and follow the API example on its model page. Usage is billed at the selected model’s rate.
06Can I estimate costs before topping up?
Yes. Use the calculator before you add funds. Top-ups start at $15. That amount adds credit to your balance, and usage draws from it at your model’s rate. Unused credit carries forward. View top-up options
07How much can cached input save?
Savings depend on the model’s cache-read rate and how many input tokens are billed at that rate. Use a measured cache hit rate from a test run to estimate your savings. Include any separate cache-write or storage charges in your budget.
Make Your First API Call
Pick a model and create your GPTProto API key. Add credit from $15 and run the quickstart on the model page. You can use the same balance to test other supported models. Unused credit stays in your account.