MiniMax • text#139 of 704 in intelligence
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,...
Data source: Artificial Analysis · ID AA: 277f939a-985b-4b37-859d-b3eabc7c0b26 · Snapshot published: 10/27/2026, 6:00:26 PM · Methodology version: 4.3
AA Intelligence Index
29.2
Artificial Analysis · 4.3 · 10/27/2026, 6:00:26 PM
Context Window
1.0M tokens
Input Price/1M
$0.30
#156 of 445
Output Price/1M
$1.20
Parameters
—
Speed
110 tok/s
#77 of 160
Latency (TTFT)
1.1s
Max Output
512K tokens
Cost per Task
$0.5076
USD / task · lower is better · Artificial Analysis · 4.3 · 10/27/2026, 6:00:26 PM
Artificial Analysis metrics for MiniMax-M3. Higher is better for capability indexes; lower is better for cost per task.
| Benchmark | Score | Maximum | Methodology | Source / version / date |
|---|---|---|---|---|
| AA Agentic Index | 29.5 | 100.0 | Artificial Analysis official API | Artificial Analysis · 4.3 · 10/27/2026 |
| Benchmark | Score | Maximum | Methodology | Source / version / date |
|---|---|---|---|---|
| AA Coding Index | 58.6 | 100.0 | Artificial Analysis official API | Artificial Analysis · 4.3 · 10/27/2026 |
| Benchmark | Score | Maximum | Methodology | Source / version / date |
|---|---|---|---|---|
| AA Cost Per Task | 0.5 | 100.0 | Artificial Analysis official API | Artificial Analysis · 4.3 · 10/27/2026 |
| Benchmark | Score | Maximum | Methodology | Source / version / date |
|---|---|---|---|---|
| AA Intelligence Index | 29.2 | 100.0 | Artificial Analysis official API | Artificial Analysis · 4.3 · 10/27/2026 |
MiniMax-M3 is an AI model developed by MiniMax, classified as a text model. It focuses on text processing and natural language generation. As a proprietary model, it is available via MiniMax's cloud API. With a context window of 1.0M tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
MiniMax-M3 is usage-based, priced at $0.3/1M input tokens and $1.2/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
MiniMax-M3 was evaluated on 4 different benchmarks, covering categories like Agentic, Coding, Cost, overall. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
MiniMax-M3 specializes in text, offering advanced capabilities for creating and processing text content.
In the 2026 AI model ecosystem, MiniMax-M3 competes directly with similarly capable models. MiniMax competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
MiniMax-M3 is an AI model developed by MiniMax. It is a text model.
MiniMax-M3 costs $0.3/1M input tokens and $1.2/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
In available benchmarks, MiniMax-M3 scored: AA Agentic Index: 29.5/100, AA Coding Index: 58.6/100, AA Cost Per Task: 0.5076/100. See the full table above for a detailed comparison.
No, MiniMax-M3 is a proprietary model from MiniMax. It is available via cloud API. For open source alternatives, check our open source model ranking.
MiniMax-M3 excels at multimodal tasks including text and vision. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: October 27, 2026 • View methodology →