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Providers

Amazon 8 Anthropic 31 Cohere 35 DeepSeek 5 Google 34 MiniMax 17 Mistral 53 Moonshot AI 18 OpenAI 106 Qwen 26 xAI 26 Xiaomi MiMo 4 Z.ai 22
MiniMax MiniMax-H3

MiniMax H3 (MiniMax)

Active

No — MiniMax H3 is not deprecated as of August 3, 2026. MiniMax has announced neither a deprecation nor a shutdown date for it.

The newest Hailuo video model, released July 2026 as a general-purpose multimodal video generator. Video is the product MiniMax is best known for outside developer circles, and the H-series numbering runs independently of the M-series language models.

The facts

Provider MiniMax
Model id MiniMax-H3
Released July 31, 2026
Deprecated not deprecated
Shutdown not published
Status Active
Last verified August 3, 2026

Frequently asked questions

Is MiniMax H3 still available?
Yes. MiniMax H3 is active and fully supported as of August 3, 2026.

Models that migrate here

MiniMax names MiniMax H3 as the replacement for 2 models.

Sources

Found something wrong? The data is one YAML file — edit it on GitHub.

This page, for machines

JSON Markdown Badge JSON

Drop the badge in a README so it turns red the day this model is retired:

[![MiniMax-H3](https://img.shields.io/endpoint?url=https://modeldeprecations.dev/badge/minimax/MiniMax-H3.json)](https://modeldeprecations.dev/minimax/MiniMax-H3)

Other MiniMax models

All MiniMax deprecations →

How to use this site

The full guide, in Markdown. Copy it and hand it to a coding agent verbatim.

# How to use modeldeprecations.dev

[modeldeprecations.dev](https://modeldeprecations.dev) answers one question per model: is it deprecated,
when does it shut down, and what replaces it. Every date on the site is cited to the
provider's own documentation, with the date we last checked it.

Three lifecycle states are used, matching the providers' own vocabulary:

- **active** — still supported, no deprecation announced.
- **deprecated** — the provider has announced it is going away. It still answers requests.
- **retired** — API access is gone. Requests fail.

A model can be active *and* carry a shutdown date: Anthropic publishes a
"not sooner than" date and Google publishes an earliest shutdown date for models
that are current and fully supported. Those are reported as scheduled shutdowns,
not deprecations, because that is what the provider actually committed to.

## Check one model

```bash
curl https://modeldeprecations.dev/api/v1/models/openai/gpt-4-32k.json
```

Or fetch the page as Markdown, which includes the answer, the dates and the sources:

```bash
curl https://modeldeprecations.dev/openai/gpt-4-32k.md
```

## Full catalog

```bash
curl https://modeldeprecations.dev/api/v1/models.json
```

Ids are `provider/model`. Dated snapshots (`gpt-4-32k-0613`) are listed as aliases of
their canonical entry rather than as separate records.

Each entry carries `computed_status`, the lifecycle state recomputed against the build
date — so a model whose shutdown has passed reads `retired` without anyone editing data.

## Badges

A shields.io endpoint per model, for READMEs that should go red when a model dies:

```
https://img.shields.io/endpoint?url=https://modeldeprecations.dev/badge/openai/gpt-4-32k.json
```

## Calendar and changelog

- Subscribe to every shutdown date: https://modeldeprecations.dev/calendar.ics
- Changelog RSS: https://modeldeprecations.dev/changelog.xml

## JSON Schema

```bash
curl https://modeldeprecations.dev/api/v1/schema.json
```

## Contribute

Data lives in YAML under `models/{provider}/{model}.yaml` in the
[GitHub repo](https://github.com/mnfst/modeldeprecations.dev). Every lifecycle date needs a source URL; CI rejects a
date without one. Open a PR.

## For agents

- Machine-readable overview: https://modeldeprecations.dev/llms.txt
- This guide plus every model inline: https://modeldeprecations.dev/llms-full.txt
- Any page also exists as Markdown: append `.md` to a model URL.
- In a browser, this site registers a **WebMCP** tool on `navigator.modelContext`:
  `check_model_deprecation`, `list_shutdowns`, `find_replacement`, and `get_usage_guide`.
- Parameters each model accepts are catalogued on the sibling site, https://modelparams.dev.