MiniMax has 1 model in The AI Leaderboard directory: MiniMax M3. This provider hub compares their verified availability, licensing, context windows, pricing references and intended uses, with direct links to every model guide.
Quick answer: MiniMax M3 is the first MiniMax model to evaluate for its documented fit: open-weight multimodal agents, long-context coding, browsing and private deployment experiments. The dedicated guide contains the full specification, evidence and deployment caveats.
MiniMax model lineup at a glance
Metric | Current directory value |
|---|---|
Models covered | 1 |
Currently ranked | None in the current top eight |
Open-weight models | 1 |
Restricted models | 0 |
Legacy or migration references | 0 |
Highest-ranked model | No current Overall rank assigned |
Last verified | September 2, 2026 |
Complete MiniMax model directory
Model names in this table link directly to their complete guides. Status and pricing can change, so confirm the active endpoint and provider terms before procurement or migration.
Model | Status | License | Context | Best fit |
|---|---|---|---|---|
Available; open-weight release announced | Open weights | Up to 1 million tokens; minimum 512K guaranteed by API documentation | open-weight multimodal agents, long-context coding, browsing and private deployment experiments |
How the MiniMax models differ
Model | Directory role | Modalities | Maximum output | Access |
|---|---|---|---|---|
MiniMax M3 | Open weights | Native text and visual understanding; text output through the language-model API | Shared within the total context limit; check the API model table for current request caps | MiniMax API, MiniMax Code, Token Plan, Hugging Face and planned local deployment resources |
The labels above describe access and lifecycle, not a hidden capability ranking. Only models with a validated Overall record receive a rank on this site. Other guides remain unranked until comparable evidence is available.
MiniMax model pricing
Model | Pricing reference | Cost caveat |
|---|---|---|
MiniMax M3 | Standard API up to 512K: $0.30 input, $0.06 cache read and $1.20 output per million tokens; rates double above 512K | Self-hosting still incurs infrastructure and operations costs |
Token price is not cost per accepted result. Measure retries, tool calls, latency, infrastructure and reviewer time on the same task set.
Which MiniMax model should you choose?
Requirement | Starting point | Why |
|---|---|---|
Highest current rank | MiniMax M3 | No ranked model; start with the documented fit and test directly |
Open weights or self-hosting | MiniMax M3 | Review the exact license, checkpoint and hardware needs |
Restricted specialist work | No restricted model in this provider directory | Use generally available models and least-privilege controls |
Migration or reproduction | MiniMax M3 | Compare current versions using pinned snapshots |
Lowest operational cost | Measure two or three eligible models | Headline token prices omit retries, tools, caching and human review |
MiniMax models, explained
MiniMax M3
MiniMax M3 was released June 1, 2026. It is listed as available; open-weight release announced with open weights. The documented context window is Up to 1 million tokens; minimum 512K guaranteed by API documentation, and the maximum output is Shared within the total context limit; check the API model table for current request caps.
- Best fit: open-weight multimodal agents, long-context coding, browsing and private deployment experiments.
- Modalities: Native text and visual understanding; text output through the language-model API.
- Access: MiniMax API, MiniMax Code, Token Plan, Hugging Face and planned local deployment resources.
- Pricing reference: Standard API up to 512K: $0.30 input, $0.06 cache read and $1.20 output per million tokens; rates double above 512K.
Read the complete MiniMax M3 guide for benchmarks, limitations, official sources and an evaluation framework.
How to evaluate MiniMax models
Shortlist the MiniMax models that meet your access, licensing and modality requirements. Freeze 20 to 50 representative tasks, then give each candidate the same prompts, tools, context, reasoning budget and retry limits. Record the exact model identifier because provider aliases can change.
Measure | Record | Decision use |
|---|---|---|
Task completion | Pass rate and rubric score | Establish whether the model meets the acceptance threshold |
Reliability | Repeated-run variance and recovery behavior | Avoid choosing from one lucky result |
Quality | Factuality, instruction following and reviewer acceptance | Separate polished output from correct output |
Tool use | Wrong calls, retries, permission errors and unsafe actions | Evaluate the model and agent harness together |
Efficiency | Wall time, tokens, caching, tools and review labor | Calculate cost per accepted result |
Governance | Retention, training, regional processing and audit logs | Confirm the deployment fits policy requirements |
Availability, versions and lifecycle
MiniMax may expose different snapshots, effort settings, products and partner integrations under similar labels. Treat every model name as incomplete without an exact endpoint or checkpoint. Re-run regression tests after any model, system prompt, retrieval, tool or permission change.
- Available means a documented access route exists, not that every region or account has access.
- Preview models can change behavior, price or retirement dates before general availability.
- Open weights require an exact license and checkpoint review; “open” does not guarantee open training data or low operating cost.
- Restricted models require separate eligibility, safeguards and data-handling review.
- Legacy models remain useful for migration and reproduction but should not be the default for a new deployment.
Sources and update policy
Official MiniMax model documentation is the provider-level starting point. Each linked model guide cites its own first-party launch page, model card, pricing reference and safety documentation.
Compare this provider with the complete Best AI Models directory.
Last verified September 2, 2026. The hub should be updated when the provider launches, retires, renames or reprices a model, changes context or output limits, alters licensing, or modifies regional availability.
Frequently asked questions
How many MiniMax models are covered?
This hub covers 1: MiniMax M3. Every model has a dedicated guide linked from the directory table and profile sections.
What is the best MiniMax model?
MiniMax does not have a model with a current Overall rank on this page. Start with MiniMax M3 for its documented fit, then validate it against alternatives using the same task set.
Does MiniMax offer open weights?
Yes. The directory identifies MiniMax M3 as open-weight options. Review the exact license, downloadable artifact and serving requirements before deployment.
How current is the pricing?
Pricing references were verified September 2, 2026 from first-party documentation summarized in each model guide. Always recheck the provider before budgeting because cache, batch, long-context, tool and regional rates can change.
Should every MiniMax model be tested?
No. Remove models that fail access, license, modality, context, latency or governance requirements first. Test the smallest credible shortlist on representative work.