# MiniMax M3.1 Flash

> Source: https://aiwiki.ai/wiki/minimax_m3_1_flash
> Updated: 2026-10-20
> Categories: AI Models, Chinese AI, Large Language Models, Reasoning Models
> License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) - attribute to "AI Wiki (aiwiki.ai)"
> Cite as: AI Wiki. "MiniMax M3.1 Flash." aiwiki.ai, 20 Oct 2026. https://aiwiki.ai/wiki/minimax_m3_1_flash
> From AI Wiki (https://aiwiki.ai), the free encyclopedia of artificial intelligence. Reuse freely with attribution.

**MiniMax M3.1 Flash** is a [large language model](https://aiwiki.ai/wiki/large_language_model) released by [MiniMax](https://aiwiki.ai/wiki/minimax) on October 19, 2026, for software development, tool-using agents and [computer use](https://aiwiki.ai/wiki/computer_use).[1] Its hosted API accepts text, images and video, and supports a one-million-token [context window](https://aiwiki.ai/wiki/context_window) with adjustable reasoning effort.[2]

## Release and model identity

MiniMax identified the anonymous model Space Bunny as an early version of M3.1 Flash and said it had processed over 200 trillion tokens. That is a company-reported usage total, not a training-data count. The launch made the model available through the API, M Plan and [MiniMax Code](https://aiwiki.ai/wiki/minimax_code).[1]

At launch, MiniMax said downloadable weights would follow later; its official social announcement scheduled them for October 23.[1][11] This remained distinct from hosted access on October 20, despite an open-weight label in the invocation guide.[2]

MiniMax's product guide describes M3.1 Flash as the generally available successor to `M3.1-Flash-Preview`. The released API identifier omits the Preview suffix. The guide's examples concern coding, financial workbooks, visual comparisons and interactive graphics. It describes image and video work as tool-assisted processing rather than native image or video generation.[9]

## API behavior

| Property | Documented behavior |
| --- | --- |
| Hosted model identifier | `MiniMax-M3.1-Flash` |
| Context capacity | 1,000,000 tokens |
| Accepted inputs | Text, images and video |
| Generated output | Text |
| Reasoning settings | `low`, `medium`, `high`, `xhigh`, `max` |
| Default effort | `max` |
| Disabling reasoning | Unsupported |

The invocation guide documents the context, input and effort settings; Artificial Analysis lists text output.[2][7] Higher effort increases reasoning-token use and latency. The API rejects requests that disable thinking or select `none` rather than treating those settings as ordinary low-effort requests.[2]

MiniMax supports two client conventions. These are compatibility interfaces operated by MiniMax, not requests served by Anthropic or OpenAI.[4][5]

| Interface | Client base URL | Effort field |
| --- | --- | --- |
| Anthropic-compatible | `https://api.minimax.io/anthropic` | `output_config.effort` |
| OpenAI-compatible Chat Completions | `https://api.minimax.io/v1` | `reasoning_effort` |

In the Anthropic-compatible interface, reasoning and answers arrive in separate content blocks. Applications continuing a tool-use conversation must retain the complete assistant content, including reasoning and tool-use blocks. The API also provides a token-counting endpoint that estimates input usage without generating a reply.[5]

### Integration limits

The OpenAI-compatible interface returns reasoning through `reasoning_content` and final text through `content`. Reasoning consumes the generation budget, so a low output limit can end a request before any final answer appears. The documentation recommends `max_completion_tokens` for new integrations.[4]

The OpenAI-compatible documentation excludes audio input. It accepts JPEG, PNG, GIF and WEBP images, plus MP4, AVI, MOV and MKV videos. Limits are 10 MB per image, 50 MB for URL or base64 video, and 64 MB per request body; Files API uploads allow videos up to 512 MB.[4]

Sampling remains fixed at `temperature` 1 and `top_p` 0.95; sending different values does not change it. `service_tier` is unsupported.[4] The Anthropic-compatible interface also ignores several otherwise familiar fields, including `stop_sequences`, `mcp_servers`, `context_management` and `container`; accepting that protocol does not supply the services those fields might represent elsewhere.[5]

## API pricing and caching

MiniMax's public price table listed the following pay-as-you-go rates on October 20, 2026. All amounts are US dollars per one million tokens, not per request or per million words.[3]

| Billing item | Price per 1 million tokens |
| --- | ---: |
| Uncached input | $0.15 |
| Output | $0.60 |
| Cached input read | $0.015 |

For example, one million uncached input tokens and one million output tokens total $0.75 at these rates, before separately charged tools. This is arithmetic from the published rates, not a fixed price for completing a task. The same pricing page lists server-side web search at $0.01 per request.[3]

[Prompt caching](https://aiwiki.ai/wiki/prompt_caching) automatically recognizes reused context without a separate caching call. Repeated system instructions, tool definitions and conversation history are examples MiniMax gives of reusable material. Usage fields report the tokens read from cache, so the discounted rate applies to actual cache hits rather than to every input token in a long conversation.[6]

## Reported evaluations

MiniMax's launch scores are vendor reports. The accompanying prose does not disclose a complete harness and budget for each result.[1]

| Evaluation | Reported result |
| --- | ---: |
| BankerToolBench | 76.2 |
| DeepSWE v1.1 | 73.7% |
| OSWorld V2 | 61.7 |
| Agents' Last Exam | 29.6 |
| CyberGym | 82% |

The CyberGym paper describes a benchmark built from 1,507 vulnerabilities across 188 software projects. Its principal task asks an agent to reproduce a vulnerability with a proof-of-concept test, given a description and codebase.[10] Consequently, a CyberGym score concerns success under a vulnerability-reproduction evaluation. It is not evidence that the model makes arbitrary software secure, or a measurement of every cybersecurity activity.

### Independent measurement

When accessed on October 20, 2026, [Artificial Analysis](https://aiwiki.ai/wiki/artificial_analysis) listed an Intelligence Index score of 43 for MiniMax-M3.1-Flash, output throughput of 93.1 tokens per second and average evaluation cost of $0.22 per Intelligence Index task. These are measurements on its evaluation service, not guaranteed latency or billing for every provider and workload.[7]

On the same page, AA-Omniscience accuracy was 56% and the non-hallucination metric, defined as 1 minus hallucination rate, was 7%.[7][8] Those are separate benchmark measures; they do not establish an error rate across all uses of the model.

The evaluator's v4.3.2 methodology combines ten evaluations, grouped into agents, coding, scientific reasoning and general tasks. It describes the suite as primarily text-based and English-language, and evaluates images, speech and multilingual performance separately.[8] The aggregate therefore should not be read as a direct test of the model's entire multimodal API or as a universal measure of reliability.

## References

1. MiniMax. "MiniMax M3.1 Flash: Redefining Agent Performance and Cost." October 19, 2026. [Official release announcement](https://www.minimax.io/blog/minimax-m31f).
2. MiniMax API Docs. "Model Invocation." Accessed October 20, 2026. [Model overview and reasoning controls](https://platform.minimax.io/docs/guides/text-generation).
3. MiniMax API Docs. "Pricing Overview." Accessed October 20, 2026. [Token and server-tool prices](https://platform.minimax.io/docs/pricing/overview).
4. MiniMax API Docs. "OpenAI SDK." Accessed October 20, 2026. [Compatibility, media limits and parameters](https://platform.minimax.io/docs/api-reference/text-openai-api).
5. MiniMax API Docs. "Anthropic SDK." Accessed October 20, 2026. [Compatibility, content blocks and token counting](https://platform.minimax.io/docs/api-reference/text-anthropic-api).
6. MiniMax API Docs. "Prompt Caching." Accessed October 20, 2026. [Caching behavior and usage accounting](https://platform.minimax.io/docs/api-reference/text-prompt-caching).
7. Artificial Analysis. "MiniMax-M3.1-Flash: Intelligence, Performance & Price Analysis." Accessed October 20, 2026. [Independent model measurements](https://artificialanalysis.ai/models/minimax-m3-1-flash).
8. Artificial Analysis. "Intelligence Benchmarking." Accessed October 20, 2026. [Intelligence Index methodology](https://artificialanalysis.ai/methodology/intelligence-benchmarking).
9. MiniMax Code. "MiniMax M3.1 Flash is Now Generally Available." Accessed October 20, 2026. [Model workflow guide and preview distinction](https://agent.minimax.io/tools/m3.1-flash).
10. Wang, Zhun, et al. "CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale." arXiv:2506.02548, June 3, 2025, revised March 24, 2026. [Research paper](https://arxiv.org/abs/2506.02548).
11. MiniMax (@MiniMax_AI). M3.1 Flash launch announcement, October 19, 2026. [Official post](https://x.com/MiniMax_AI/status/2112150867868541221).