Requesty

minimax-m3.1-flash

MiniMax/🇸🇬 Singapore/chat

MiniMax M3.1 Flash is a fast multimodal model in the MiniMax M3 family, built for agentic cowork automation, coding and visual tasks. It scores 72.5% on AutomationBench AA (best among open models), 73.67% on DeepSWE, 91.0 on BabyVision with tools, 82.5 on CharXiv RQ, 56% on AA Omniscience and 48% on HLE. Supports image input, tool calling, structured JSON output, reasoning and prompt caching. Ideal for multi step workflows, coding agents, frontend and presentation generation, and professional analysis at low cost.More
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Which id to call

minimaxi/minimax-m3.1-flash

This exact deployment on MiniMax, with no routing and no failover. Send it as the model field.

Input /1M

$0.15

$0.01 cached

Output /1M

$0.60

4.0x input

Context

1M

128K output

Added

Oct 2026

chat

Capabilities 5/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What minimax-m3.1-flash costs

Provider prices per 1M tokens, updated October 20, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$0.15

Output /1M

$0.60

Cache write /1M

-

Cache read /1M

$0.01

What a workload costs

100K input + 10K output
$0.0210
1M input + 100K output
$0.21
10M input + 1M output
$2.10

At the rates above, before caching. A cache read costs $0.01 per 1M, so repeated context lands under these figures.

model=

Which id to call

One base url, https://router.requesty.ai/v1, and one key for every id here.

minimaxi/minimax-m3.1-flash

This exact deployment on MiniMax, with no routing and no failover. Send it as the model field.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.

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from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="minimaxi/minimax-m3.1-flash", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window1M tokens
Max output128K tokens
API typechat
AddedOct 2026
Model id
Data retentionNone
Used for trainingNo
Served from🇸🇬 Singapore

Released 2026-10-19

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

Intelligence Indexreasoning
42.7%

Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.

Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.

Same provider

More from MiniMax

Newest first, on the same provider and the same key.

Reference

minimax-m3.1-flash questions

How much does minimax-m3.1-flash cost?

minimax-m3.1-flash is priced at $0.15 per million input tokens and $0.60 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of minimax-m3.1-flash?

minimax-m3.1-flash has a context window of 1M tokens, with a maximum output of 128K tokens per response. That's roughly 1,333 words of input you can fit in a single prompt.

How does minimax-m3.1-flash perform on benchmarks?

minimax-m3.1-flash scores 53.4% on SciCode, 48.0% on Humanity's Last Exam, 42.7% on Intelligence Index. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.

What can minimax-m3.1-flash do?

minimax-m3.1-flash supports vision input, tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use minimax-m3.1-flash with the OpenAI SDK?

Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "minimaxi/minimax-m3.1-flash". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run minimax-m3.1-flash through Requesty?

Yes. minimax-m3.1-flash runs through Requesty's OpenAI-compatible API, served from MiniMax. You do not host the model yourself: point base_url at Requesty, set the model to "minimaxi/minimax-m3.1-flash", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call minimax-m3.1-flash through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.

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