LLMminimax

MiniMax: MiniMax M3

MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...

Anyone in the Project can @-mention MiniMax: MiniMax M3 with the team's shared context - pooled credits, one chat, one memory.

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Starter is free forever - 1 Project, 100 credits/month, 1 MCP. No card.

Verdict

MiniMax M3 offers a massive 524K token context window at aggressive pricing — $0.30 input makes it one of the cheapest options for long-context work. It handles text, image, and video inputs, positioning it as a multimodal generalist. The lack of public benchmark data means you're flying blind on quality relative to peers like GPT-4o or Claude. Best for teams willing to test-drive a cost-effective long-context model where price matters more than proven performance.

Best for

Budget-conscious long-context document analysis
Multimodal prototyping with video inputs
High-volume text processing workflows
Exploratory projects with flexible quality needs

Strengths

The 524K context window rivals Gemini 1.5 Pro while undercutting most competitors on input cost. Multimodal support spanning text, image, and video gives you flexibility for mixed-media tasks without switching models. The $0.30/Mtok input rate makes it viable for batch processing large corpora where token volume would bankrupt other options. Video understanding capability is rare at this price point.

Trade-offs

Zero public benchmarks means no MMLU, HumanEval, or GPQA scores to gauge reasoning quality against known baselines. You'll need to run your own evals before committing production workloads. Output pricing at $1.20/Mtok is 4x the input rate — fine for summarization, painful for generation-heavy tasks. The model's recency and lack of community adoption mean fewer integration examples and troubleshooting resources compared to OpenAI or Anthropic offerings.

Specifications

Provider: minimax
Category: llm
Context length: 524,288 tokens
Max output: 512,000 tokens
Modalities: text, image, video
License: proprietary
Released: 2026-05-31

Pricing

Input: $0.30/Mtok
Output: $1.20/Mtok
Model ID: minimax/minimax-m3

Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool - one plan, one balance for everyone.

Team cost calculator

Seats5 peopleMessages / seat / day80Avg turn size2 ktokOutput share30 %

Estimated monthly spend

$10.03

17.6M tokens / month
5 seats · 80 msgs/day

Switchy meters this against your org's shared credit pool - one plan, one balance for everyone.

Providers

Provider	Context	Input	Output	P50 latency	Throughput	30d uptime
minimax	524k	$0.30/Mtok	$1.20/Mtok	—	—	—

Performance

Performance snapshots are collected daily. Check back after the next ingestion run.

Benchmarks

Public benchmark scores are not available yet for this model. Check back after the next ingestion run.

Works well with

Top MCPs

Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.

How Switchy teams use it

Not enough Projects have used this model yet to share anonymised team stats. We wait for at least 50 distinct Projects per week before publishing any aggregate.

Starter prompts

Summarize Long Transcript

Read this full transcript and produce a structured summary with three sections: Key Decisions, Action Items with owners, and Open Questions. Focus on what requires follow-up.

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Analyze Video Content

Watch this product demo video and list: 1) main features shown, 2) UI elements highlighted, 3) customer pain points addressed. Note timestamps for each.

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Compare Document Versions

Here are two versions of a contract. List every substantive change between them, organized by section. Flag any new obligations or liability shifts.

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Extract Data from Images

Extract all line items from these invoice images into a JSON array with fields: description, quantity, unit_price, total. Flag any illegible entries.

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Batch Process Research Papers

For each paper below, write a 150-word abstract covering: research question, methodology, key findings, and implications. Maintain academic tone.

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Compare with

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