How much does MiniMax M2.7 cost?

MiniMax M2.7 costs $0.21/M input tokens and $0.84/M output tokens, with separate rates for Cache Read at $0.042/M tokens.

What is the context length of MiniMax M2.7?

MiniMax M2.7 has a 196,608 token context window.

Does MiniMax M2.7 support tool calling and structured outputs?

Yes. MiniMax M2.7 accepts tools and tool_choice for function calling. It supports response_format for JSON output, without JSON-schema enforcement.

Which providers serve MiniMax M2.7?

MiniMax M2.7 is served by 2 providers on OpenRouter: GMICloud and Groq. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

When was MiniMax M2.7 released?

MiniMax M2.7 was released on March 18, 2026.

MiniMax: MiniMax M2.7

minimax/minimax-m2.7

Model weights

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MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent collaboration, enabling it to plan, execute, and refine complex tasks across dynamic environments.

Trained for production-grade performance, M2.7 handles workflows such as live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. It delivers strong results on benchmarks including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while achieving a 1495 ELO on GDPval-AA, setting a new standard for multi-agent systems operating in real-world digital workflows.

Modalities

In / out price

30% off

$0.21 / $0.84per 1M

Context

197K

Released

Mar 18, 2026

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Latency / throughput


30% off	$0.30$0.21	$1.20$0.84	$0.06$0.042	1.33s	40 tok/s	99.80%
	$0.60	$1.80	--	0.66s	198 tok/s	99.43%

Input $0.21Output $0.84
30% off
40 tok/s99.80% uptime
Input $0.60Output $1.80
198 tok/s99.43% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.1876/M tokens

Output

$1.113/M tokens

MiniMax M2.7 — Price history

Price history

No effective price data for this selection

		$0.0603	$0.839	89.1%	76.3%
		$0.6000	$1.799	86.7%	23.7%

Effective in $0.0603Effective out $0.839
Token share
76.3%
Effective in $0.6000Effective out $1.799
Token share
23.7%

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Throughput

198tok/s

P50, best across providers

Latency

0.66s

P50, best provider

Latency / throughput

AutoExacto benchmarks

GPQA DiamondTAU-BenchGroq89.3%74.2%auto-routing86.6%71.8%AtlasCloud86.0%72.0%GMICloud87.2%70.8%MiniMax85.8%71.4%MiniMax85.8%68.6%

+1 more providers

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

99.54%

Availability over the last 3 days

Last 72 hours

Availability 99.54%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.73%

Without Routing

95.39%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for MiniMax: MiniMax M2.7 (Artificial Analysis, Design Arena and Vals AI)
Source	Benchmark	Score
Artificial Analysis	MiniMax-M2.7 Coding Index	52.6
Artificial Analysis	MiniMax-M2.7 Agentic Index	15.3
Artificial Analysis	MiniMax-M2.7 GPQA Diamond	87.4%
Artificial Analysis	MiniMax-M2.7 HLE	29.6%
Artificial Analysis	MiniMax-M2.7 IFBench	75.7%
Artificial Analysis	MiniMax-M2.7 τ²-Bench Telecom	84.8%
Artificial Analysis	MiniMax-M2.7 AA-LCR	78.3%
Artificial Analysis	MiniMax-M2.7 τ-Bench Banking	9.9%
Artificial Analysis	MiniMax-M2.7 GDPval-AA	25.8%
Artificial Analysis	MiniMax-M2.7 CritPt	0.6%
Artificial Analysis	MiniMax-M2.7 SciCode	50.1%
Artificial Analysis	MiniMax-M2.7 Terminal-Bench Hard	39.4%
Artificial Analysis	MiniMax-M2.7 Terminal-Bench 4.0	0.0%
Artificial Analysis	MiniMax-M2.7 Terminal-Bench 2.1	55.4%
Design Arena	MiniMax M2.7 Models Arena 3D Elo	1175
Design Arena	MiniMax M2.7 Models Arena Asciiart Elo	1129
Design Arena	MiniMax M2.7 Models Arena Code Categories Elo	1223
Design Arena	MiniMax M2.7 Models Arena Data Visualization Elo	1230
Design Arena	MiniMax M2.7 Models Arena Game Development Elo	1198
Design Arena	MiniMax M2.7 Models Arena SVG Elo	1123
Design Arena	MiniMax M2.7 Models Arena UI Component Elo	1202
Design Arena	MiniMax M2.7 Models Arena Website Elo	1234
Vals AI	MiniMax-M2.7 AIME	91.0%
Vals AI	MiniMax-M2.7 CaseLaw v2	60.9%
Vals AI	MiniMax-M2.7 Code Migration	8.7%
Vals AI	MiniMax-M2.7 CorpFin v2	61.2%
Vals AI	MiniMax-M2.7 EMB	28.5%
Vals AI	MiniMax-M2.7 Finance Agent (v2)	27.9%
Vals AI	MiniMax-M2.7 GPQA Diamond	86.6%
Vals AI	MiniMax-M2.7 Harvey's Legal Agent Benchmark v1	0.0%
Vals AI	MiniMax-M2.7 IOI v1	4.9%
Vals AI	MiniMax-M2.7 LiveCodeBench	79.9%
Vals AI	MiniMax-M2.7 LegalBench	84.0%
Vals AI	MiniMax-M2.7 Legal Research Bench	10.6%
Vals AI	MiniMax-M2.7 MedCode	34.4%
Vals AI	MiniMax-M2.7 MedScribe	79.9%
Vals AI	MiniMax-M2.7 MMLU Pro	80.4%
Vals AI	MiniMax-M2.7 ProgramBench	0.0%
Vals AI	MiniMax-M2.7 ProofBench v1	3.0%
Vals AI	MiniMax-M2.7 SWE-bench	73.8%
Vals AI	MiniMax-M2.7 Tax Agent Bench	6.9%
Vals AI	MiniMax-M2.7 TaxEval v2	66.6%
Vals AI	MiniMax-M2.7 Terminal-Bench 2.1	48.7%
Vals AI	MiniMax-M2.7 Vals Index	24.6%
Vals AI	MiniMax-M2.7 Vibe Code Bench v1.1	11.9%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

There are many coding agents, but this one is yours.

10.9Btokens

Hermes Agent

Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.

9.35Btokens

OpenClaw

OpenClaw is an open-source AI agent that connects to your messaging apps and takes real actions on your behalf, from running commands and browsing the web to managing files and sending emails.

8.06Btokens

TheOne陪伴

new

1.58Btokens

Claude Code

Claude Code is Anthropic's agentic coding tool that reads your entire codebase, plans and executes changes across files, runs tests, and iterates on failures, all from natural language prompts.

1.2Btokens

Top 5 Apps

5.18B

Rest of OpenRouter

674M

Not currently available through EU in-region routing. In-region routing docs

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Providers