Saving Money on AI APIs? Start With These 30 Models

Saving Money on AI APIs? Start With These 30 Models

I'll be honest with you. When I finished my coding bootcamp, I thought I had this whole AI thing figured out. I knew how to call an API. I knew what a token was (kind of). I figured I could just plug GPT-4o into my side projects and call it a day.

Then I got my first bill.

It wasn't huge, but it was bigger than I expected, and that's when I went down this rabbit hole of trying to figure out if there were cheaper options out there. What I found honestly blew my mind. There are dozens of AI models, and some of them cost literally 100x less than the popular ones. Let me walk you through everything I learned.

Here's the thing nobody tells you in bootcamp. When you're building a product that talks to an AI model, every single request costs money. And those costs add up fast.

I was paying around $3.50 per million output tokens for one of the top-tier models. Sounds cheap on paper, right? But my little chatbot project was generating thousands of tokens per conversation. The math got ugly fast.

So I started hunting around. I found this thing called Global API, which is basically a unified gateway that gives you access to a ton of different AI models through one API endpoint. Same code, different models. Switch them out with one parameter. I had no idea this was even a thing.

What really shocked me was seeing the price spread. Some models cost $0.01 per million output tokens. Others cost $3.50. Same kind of task. Wild.

After staring at pricing pages for way too long, I started grouping models into rough buckets based on how much they cost. This helped me figure out which one to use for which kind of job.

I was floored by this category. Models like Qwen3-8B, GLM-4-9B, Qwen2.5-7B, and GLM-4.5-Air all clock in at a single cent per million output tokens. One cent. You could run thousands of requests for basically nothing.

These tiny models are perfect for simple stuff. Think basic question-answering, classifying text, or just kicking the tires on an idea before you commit to building something serious. Qwen3.5-4B is also in this range at $0.05, and it's great when you need responses lightning fast.

If you're a bootcamp grad like me and you're just experimenting, start here. I burned through maybe $0.50 testing my ideas on these models. Try doing that with a $3.50 model and you'll feel it.

This is where I landed for most of my projects. You get noticeably better answers without paying through the nose.

DeepSeek V4 Flash sits at $0.25 per million output tokens and honestly changed the game for me. The input cost is just $0.18, and it has a 128K context window. For most things I'm building, this is more than enough horsepower.

Other models I fell in love with in this range:

The Ga-Economy one is interesting because it's a "routing" model that automatically picks the cheapest model that'll do the job. Kind of like a smart switchboard. Pretty neat if you don't want to think too hard about which model to use.

When you need something more serious, this tier delivers without breaking the bank. Production apps and coding assistants live here.

Qwen2.5-72B runs at $0.40 (input $0.20) and handles larger workloads well. DeepSeek-V3.2 is $0.38 (input $0.35), and Doubao-Seed-Lite is $0.40 (input $0.10).

For vision tasks, Qwen3-VL-32B is at $0.52 (input $0.26). If you want something multimodal, Qwen3-Omni-30B sits at $0.52 (input $0.30).

GLM-4-32B at $0.56 (input $0.26) is solid for harder reasoning problems. Hunyuan-Turbo at $0.57 (input $0.18) is what I'd call a balanced all-rounder.

These models cost more but pack a punch. When you need complex reasoning or you're building enterprise stuff, this is where you look.

GLM-4.6V for vision costs $0.80 (input $0.39). Doubao-Seed-1.6 is also $0.80 (input $0.05) and has a 128K context window. DeepSeek V4 Pro runs at $0.78 (input $0.57) with 128K context, which is solid for a premium DeepSeek option.

These are the flagship models. The ones with the longest context windows and the most advanced reasoning. Think of these as the Ferraris of the AI world.

Models like DeepSeek-R1, Kimi K2.5, Kimi K2.6, and Qwen3.5-397B live here. I haven't actually needed them for any of my projects yet, but it's good to know they're there if I ever build something that needs serious brainpower.

Okay so here's where it gets fun. The actual code. Since Global API gives you one endpoint for everything, switching models is just changing a string in your request. Let me show you the basic setup I use:

import requests

API_KEY = "your-global-api-key-here"
BASE_URL = "https://global-apis.com/v1"

def chat_with_model(model_name, user_message):
    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }

    payload = {
        "model": model_name,
        "messages": [
            {"role": "user", "content": user_message}
        ]
    }

    response = requests.post(
        f"{BASE_URL}/chat/completions",
        headers=headers,
        json=payload
    )

    return response.json()

result = chat_with_model("qwen3-8b", "What's the capital of France?")
print(result["choices"][0]["message"]["content"])

See how clean that is? You change "qwen3-8b"

to "deepseek-v4-flash"

or "glm-4-9b"

and you're good to go. No new SDK, no new authentication. Same code.

Here's a slightly fancier version where I compare responses from a cheap model and a pricier one side by side:

def compare_models(prompt):
    cheap_model = "qwen3-8b"  # $0.01/M output
    fancy_model = "deepseek-v4-flash"  # $0.25/M output

    cheap_response = chat_with_model(cheap_model, prompt)
    fancy_response = chat_with_model(fancy_model, prompt)

    print("=== Cheap Model Says ===")
    print(cheap_response["choices"][0]["message"]["content"])
    print("\n=== Fancy Model Says ===")
    print(fancy_response["choices"][0]["message"]["content"])

compare_models("Explain async/await in Python like I'm five")

I ran something like this during testing and honestly, for simple stuff, the $0.01 model held its own. For more nuanced questions, the $0.25 model gave better answers. Knowing when to use which saves real money.

Let me share what I learned about the different companies making these models. It helped me decide who to trust with my projects.

I had no idea DeepSeek was this good until I dug in. They're basically the value kings right now. DeepSeek V4 Flash at $0.25 per million output tokens is the standout. You get near-flagship quality at a budget price. Their newer DeepSeek-V3.2 is $0.38, and DeepSeek V4 Pro is $0.78 for when you need extra muscle. They also have the R1 thinking model in the premium tier.

Qwen has models at literally every price point. I counted at least ten of them on the list. The tiny Qwen3-8B for $0.01, mid-size workhorses like Qwen3-32B at $0.28, and big boys like Qwen2.5-72B at $0.40. They also do vision (Qwen3-VL-32B) and multimodal (** Qwen3-Omni-30B**). If you're not sure where to start, Qwen is a safe bet.

GLM has some of the cheapest options out there. GLM-4-9B at $0.01 is one of my go-to testing models. GLM-4.5-Air is also $0.01 for output. For bigger tasks, GLM-4-32B at $0.56 handles harder reasoning well. And if you need vision, GLM-4.6V is $0.80.

Tencent makes the Hunyuan line, and they have solid options across the board. Hunyuan-Lite is $0.10, Hunyuan-Standard and Hunyuan-Pro are both $0.20, and Hunyuan-TurboS is $0.28. The Hunyuan-Turbo at $0.57 is what I'd use when I need a balanced all-rounder for production.

ByteDance's Doubao models are interesting. ByteDance-Seed-OSS at $0.20 is great for open-source-style workloads. Doubao-Seed-Lite at $0.40 is their budget play. Doubao-Seed-1.6 at $0.80 with a 128K context window is their classic option.

Baidu's ERNIE-Speed-128K caught my eye because it has a 128K context window and costs $0.20 per million output tokens. The input is literally $0.00. If you're processing long documents, this one deserves a look.

These are smaller players but worth knowing about. Step-3.5-Flash at $0.15 is fast and cheap. Ling-Flash-2.0 from InclusionAI is $0.50 and great when you need lightweight speed.

This one's unique. GA Routing makes "router" models that automatically pick the best underlying model for your task. Ga-Economy is $0.13 and routes to the cheapest option that can handle your request. Ga-Standard is $0.20 for mid-tier routing. If you don't want to think about model selection, this is a lazy-but-smart choice.

Here's the full breakdown of all 30 models I looked at, sorted from cheapest to most expensive output cost. This is the data that made me realize how much I was leaving on the table: