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minimax-m3.1-flashMiniMax

in /1M$0.15input tokens
out /1M$0.60output tokens
context1M128K out
median ttft1.46smeasured
api
chat
hosting
Singapore
model lab
MiniMax
weights
open
added
October 2026
model id
minimaxi/minimax-m3.1-flash

capabilities 5/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

2 providers serve minimax-m3.1-flash. This page is one of them. Compare all endpoints

pricing

no markup
input
$0.15
output
$0.60
cache write
-
cache read
$0.01

worked cost

Estimated cost for three request volumes
volumecost
100K in + 10K out$0.0210
1M in + 100K out$0.21
10M in + 1M out$2.10

Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing

provider price, passed throughper 1M tokens

measured

through Nov 2
median ttft
1.46s
median tok/s
164.0
blended /1M
$0.02
cache hit
97.9%

Weekly aggregates from production traffic routed through Requesty to this endpoint. A metric with no qualifying sample is left out rather than filled in. Compare against the other providers

benchmarks

artificial analysis
Benchmark scores, each normalised to 100
evalScore as a share of 100/100
SciCode53.4
Humanity's Last Exam48.0
Intelligence Index28.9
3 evalsmean43.4

Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2026-10-19.

policy

data terms
retention
none
trains on prompts
no
hosted in
Singapore

Terms are the provider's, not Requesty's: routing a request here puts it under them. MiniMax Privacy Policy

Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.

quickstart

openai compatible
minimaxi/minimax-m3.1-flash

this id pins the minimax deployment, with no routing and no failover. the managed id on the canonical page routes across all 2 providers instead

main.py
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)

Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models

notes

reference

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.

questions 6

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. Requesty charges exactly what the upstream provider charges, we don't add markup.
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 is 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, 28.9% on Intelligence Index. The benchmarks pane shows every published result, each normalised to 100.
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 pane 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.

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call minimax-m3.1-flash through one endpoint

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

minimax-m3.1-flashminimaxin $0.15 /1Mout $0.60 /1Mctx 1Mttft 1.46shosted Singapore2 providers serve this model