MiniMax M2.7 Pricing

    OSS

    As of August 25, 2026, MiniMax M2.7 API pricing is $0.30 per million input tokens and $1.20 per million output tokens. A typical 100K-in / 20K-out request costs $0.05. Source: https://anotherwrapper.com/tools/llm-pricing

    Source: AnotherWrapper LLM pricing (https://anotherwrapper.com/tools/llm-pricing)

    Updated August 25, 2026204.8K context$1.50 blended / 1M

    Input $/M

    $0.30

    Output $/M

    $1.20

    Blended / 1M

    $1.50

    100K / 20K request

    $0.05

    Where it ranks

    Percentile against every model with a published score on that eval. Click a row for the full board.

    Quality vs price

    GPQA Diamond against blended input+output $/M. Log price. MiniMax M2.7 is the green point.

    MiniMax M2.7 specs

    Context Window204.8K
    Max Output196.6K tokens
    Release Date2026-03-18
    Knowledge CutoffN/A
    LicenseOpen Source
    Throughput41.8 tok/s

    MiniMax M2.7 benchmarks

    Compare MiniMax M2.7

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    MiniMax M2.7 FAQ

    How much does MiniMax M2.7 cost per million tokens?

    As of August 25, 2026, MiniMax M2.7 MiniMax API pricing is $0.30 per million input tokens and $1.20 per million output tokens. Input tokens are the prompt you send; output tokens are the completion. Long answers therefore cost more than short ones even when the prompt stays the same. Source: https://anotherwrapper.com/tools/llm-pricing

    What is the blended API cost for MiniMax M2.7?

    On this page the blended MiniMax M2.7 API cost is $1.50 for 1 million input tokens plus 1 million output tokens. That 1:1 mix is the comparison scale used across the LLM pricing table. A 3:1 mix (three million input tokens per one million output tokens), which some calculators use, would be about $2.10.

    How much does a typical MiniMax M2.7 request cost?

    A typical MiniMax M2.7 API request with 100K input tokens and 20K output tokens costs about $0.05 at current rates as of August 25, 2026. Multiply that by daily or monthly volume to estimate spend. Caching, batch APIs, and volume discounts from MiniMax can bring the real invoice lower than the public list rate at https://anotherwrapper.com/tools/llm-pricing.

    What is the context window for MiniMax M2.7?

    MiniMax M2.7 supports a 205K token context window and can generate up to 197K output tokens per request. The context window is the total prompt plus conversation history the model can see in one call. Larger windows cost more when you fill them, because every input token is billed per million tokens.

    Is MiniMax M2.7 open source?

    Yes. MiniMax M2.7 is an open-weight model by MiniMax. You can download the weights and self-host, or pay MiniMax's hosted API and skip GPU ops. Hosted API pricing on this page is the public per-million-token rate, not the electricity cost of running the weights yourself.

    What benchmarks does MiniMax M2.7 perform well on?

    MiniMax M2.7 currently reports GPQA Diamond 86.6%, SWE-bench Verified 73.8%, DeepSWE 0.2%. See the performance table for the full eval set. Use those scores with the token prices above when you are choosing between a cheaper LLM and a frontier model. GPQA, SWE-bench, and HLE are the evals people usually compare first.

    Is MiniMax M2.7 good for coding?

    MiniMax M2.7 scores 73.8% on SWE-bench Verified. Pair that score with MiniMax API pricing on this page: a slightly worse SWE-bench model can still win if it is much cheaper per million tokens. Open the SWE-bench or coding leaderboard from the sidebar for the full ranking, then jump into an LLM comparison against a coding specialist.

    How do I compare MiniMax M2.7 with another LLM?

    Use the Compare picker on this page to start an LLM comparison. Search by model or provider, pick a second model, and AnotherWrapper opens a dedicated MiniMax M2.7 vs page with per-million-token prices, blended 1M-in / 1M-out cost, context window, throughput, and benchmarks. You can also open any model from the sidebar, or go back to the LLM pricing table to sort the full index.

    What are the cheapest alternatives to MiniMax M2.7?

    The cheapest LLM alternative depends on whether you optimize for blended token cost, coding evals, or context window. Start with the popular matchups on this page, then sort the LLM pricing table by blended cost to see which hosted APIs undercut MiniMax M2.7. Open-weight models can be cheaper still if you self-host, but that is not the same as MiniMax API pricing on this page.

    How do I use MiniMax M2.7 in my application?

    MiniMax M2.7 is called through MiniMax's API with an API key. Bill against input and output tokens separately; cache or shorten prompts if spend is high. If you are shipping a full product, AnotherWrapper includes pre-built API routes and templates for MiniMax and 5+ other providers with auth, payments, and deployment already configured.

    How accurate is this MiniMax M2.7 pricing data?

    This MiniMax M2.7 page tracks the latest published MiniMax API pricing from MiniMax, quoted per million tokens. List rates can differ from invoices because of prompt caching, batch discounts, committed-use tiers, and private contracts. Official rate sheet: https://anotherwrapper.com/tools/llm-pricing. Benchmark scores come from official publications and independent evals, not from a private lab run by AnotherWrapper.

    How fast is MiniMax M2.7?

    MiniMax M2.7 has a measured throughput of about 41.8 tokens per second (tok/s). Throughput is how fast completions stream once the model starts generating; time-to-first-token can still lag under load. Faster APIs matter when you are building chat or agents, even if the per-million-token price is the same.

    About MiniMax M2.7 API pricing

    MiniMax M2.7 is a open-source model from MiniMax. Current API pricing is $0.30 per million input tokens and $1.20 per million output tokens, with a 204.8K token context window. A blended 1M-in / 1M-out workload costs $1.50.

    Rank it on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.

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