MiniMax-H3-Image explained: the open-weight 16-megapixel image model, its price, hardware and licence

This page is the free part.

The course goes deeper on how to serve a large open model and work out what it costs

₹1,333 in India/$35 everywhere elseonce, for the whole course

The Generative AI and Agentic AI course covers how to serve a large open model and work out what it costs across a run of lessons, not one page. These 4 alone are about 270 minutes of step-by-step reading, every one with code you run in the browser, all with a quiz.

1. Model Serving and Inference APIs: Turning a Model File Into a Service

   How a trained model becomes a live API. Covers online vs batch serving, REST vs gRPC, dynamic batching, autoscaling and p99, with a batch simulator.

   60 min · diagrams · code you run · quizfree to read now

2. Cost per Prediction: What Do 1,000 Answers Really Cost?

   I rented five small computers from Amazon, one at a time, each with one core. On each, I found the most questions a second it could answer while 99 in 100 answers came back within 25 thousandths of a second. I tried answering one question at a time, and in small groups. Then I divided each computer's price per hour by the answers it gave in an hour. The cheapest computer per hour, the a1.medium, was the dearest per answer: $0.0385 per million answers one at a time. The newest Graviton chip, in the c8g.medium, was the cheapest: $0.0078 per million one at a time and $0.0025 in groups. Groups gave every computer 3.0 to 4.6 times the answers. The test program shared each computer's one core, 4 to 9% of it one at a time and 13 to 19% in groups, so all these rates are a little low. A real shop is quiet much of the day, so it pays for idle hours. All five computers gave identical scores. Every AWS step of the first computer is recorded; the other four ran the same steps from a script, shown.

   84 min · diagrams · code you run · quiz

3. Quantization: The Same Model in Fewer Bits

   The same Qwen2.5 3B model stored three ways and measured on a laptop: 6.18 GB at 16 bits per weight, 3.29 GB at 8.5 and 1.93 GB at about 5. The 8-bit file kept the 16-bit file's top next word on 24 of 24 prompts and got the same 33 of 40 sums right; the 5-bit file kept 19 of 24, all 5 changes on near ties. Writing speed went from 11.1 to 18.3 to 28.4 tokens a second, while reading barely changed.

   46 min · diagrams · code you run · quiz

4. Reading a Model Name: What 27B, FP8, A3B and Instruct Actually Mean

   A model name is a spec sheet written in shorthand. Learn to decode publisher, family, version, parameter count, mixture-of-experts markers, post-training suffixes and numeric formats, and to predict from the name alone whether a model will fit on your GPU.

   80 min · diagrams · code you run · quizfree to read now

pay once,
yours for life