MiniMax M3.1 Flash API pricing

By the aitokensai editors · Verified 2026-10-31 Sources: MiniMax API pricing

MiniMax's M3.1 flash tier (very low rate for high-frequency calls). Available at listed at platform rate (no published official USD price).

USD, standard tier. Rate read from the live rate config on 2026-10-31. MiniMax publishes no USD list price for this model, so nothing here is cross-checked against one — this is a gateway rate, not a discount.

Specifications

What MiniMax M3.1 Flash costs at your volume

Calculated at $0.075 input / $0.3 output per 1M tokens, 4.0× apart on this model, assuming a 5:1 input-to-output ratio. That ratio is the single largest source of error in this table: resend-heavy workloads drift well past it, and at 4.0× the correction is not linear. The cost calculator takes the actual figures.

What MiniMax M3.1 Flash is for

$0.075 per million input tokens puts MiniMax M3.1 Flash low enough that volume stops being the first question. This is a model you can point at thousands of calls a day and not think about: summarisation at scale, autocomplete, extraction pipelines, tier-one filtering in front of a stronger model.

Two honest limits. At 4.0×, output is still the majority of the bill, so this is not the cheapest option for genuinely long generation. And at this price the saving from staying cheap is small — escalating a hard case to a flagship costs pennies next to the cost of getting it wrong.

Where MiniMax M3.1 Flash sits in the index

MiniMax M3.1 Flash is 25 of 226 on input rate and 36 of 226 on output rate. A gap of 11 places, because on this model the output rate is 4.0× the input rate, level with the index median of 4.0× An output-heavy workload therefore leaves it almost where it started, which is why the cheapest model per input token is routinely not the cheapest per task. Percentile is the share of the 226 models in this index that cost more than MiniMax M3.1 Flash.

On an agent mix the lowest blended rate in the same index is Gemma2 9B It at $0.01 per 1M tokens, about 24.4× less than this model at the same ratio. Across the whole index, sorting by input price alone moves a model by as much as 74 places; on MiniMax M3.1 Flash specifically the shift is 11 — which is what the re-ranked index exists to show.

MiniMax M3.1 Flash is 25 of 226 across every model in the index; the comparison that usually settles a choice is MiniMax's own lineup further down.

MiniMax M3.1 Flash among MiniMax's 2 models

MiniMax M3.1 Flash is the cheapest of MiniMax's 2 models in this index at $0.075 per 1M input tokens. The range inside that group runs from MiniMax M3.1 Flash at $0.075 to MiniMax M3 at $0.15. A spread of 2×, and every other model in the group costs more on input than this one.

On input rate alone, stepping up to MiniMax M3 costs 2.0× the input rate. Both measured at 2026-10-31, the same check as every other rate on this page.

Full MiniMax range, including models outside this shortlist: MiniMax rate index.

Similarly priced alternatives

Blended comparison (input + output per 1M). Price is one axis These are the three closest to MiniMax M3.1 Flash in blended rate, not interchangeable substitutes for it.

Calling MiniMax M3.1 Flash

The identifier you send is MiniMax-M3.1-Flash. Copy it exactly, because a mismatch returns a model error rather than a connection error, which sends most people to debug the wrong thing. Everything else is a base URL argument (MiniMax M3).1 Flash's own SDKs work unchanged.

from openai import OpenAI

client = OpenAI(base_url="https://aicomp.ai/v1", api_key="sk-...")

resp = client.chat.completions.create(
    model="MiniMax-M3.1-Flash",
    messages=[
        {"role": "system", "content": "Answer in one short paragraph."},
        {"role": "user", "content": "Explain what changed in this release."},
    ],
    max_tokens=300,
)

# prompt_tokens / completion_tokens 是真实账单的唯一依据 —— 记下来，别猜
print(resp.usage.prompt_tokens, resp.usage.completion_tokens)

Log the usage object on every call, not just while you are optimising. On MiniMax M3.1 Flash output costs 4.0× what input costs, so the same monthly token count bills very differently depending on how much of it comes back as output — measure your own split before extrapolating from the headline input rate, because rates move with vendor promotions.

Setting it up

Pointing an existing integration at MiniMax M3.1 Flash is a base URL change, not a rewrite. Pick your tool:

• Claude Code — set the base URL via environment variables
• Cursor — override the API endpoint in settings
• OpenAI / Anthropic SDK — one base_url argument
• Python, sync, streaming and async examples
• Cutting the bill — eight levers ranked by effect

What different usage shapes cost on MiniMax M3.1 Flash

A monthly token budget does not convert cleanly into a monthly invoice, and MiniMax M3.1 Flash is an ordinary case rather than an extreme one: output is priced at 4.0× input, level with the median of 4.0× across the 226 models in our index. Everything follows from that one number At 5:1 it is manageable, at 1:1 the same token count costs half as much. Below are five shapes real MiniMax M3.1 Flash deployments fall into, each costing it out at the split it actually produces.

The cheapest comparison is GPT-5 nano at $0.025 / $0.2 per 1M — 1.7× cheaper than MiniMax M3.1 Flash on a blended rate. Treat it as a rate floor, not a recommendation: it says nothing about whether GPT-5 nano can do the work you need MiniMax M3.1 Flash for.

Read the table as a sanity check rather than a forecast. If your own output share sits anywhere near 3%, everything above is priced almost entirely at MiniMax M3.1 Flash's $0.075 input rate; at 40% the $0.3 output rate has taken the larger half. Nobody's split is exactly the one you assumed when you picked the model, which is why the calculator asks for it before quoting anything.

FAQ

Get MiniMax M3.1 Flash access