MiniMax-M2.7
MiniMaxMiniMaxOpen WeightMIT · Commercial OK
Description
MiniMax M2.7 features model self-improvement driving productivity innovation. It builds complex agent harnesses independently to accomplish highly complex productivity tasks. M2.7 demonstrates excellent performance in real-world software engineering including end-to-end project delivery, log analysis, code security, and ML tasks. On SWE-Pro it scores 56.22%, nearly matching Opus. It excels in professional office domains achieving the highest ELO among open-source models on GDPval-AA (1495), with significant improvement in complex editing for Office Suite. M2.7 maintains 97% skill adherence on 40 complex skills cases.
Release Date
2026-03-18
Parameters
—
Context Length
205K
Modalities
text
Capability Radar
24
general
52
coding
87
reasoning
63
science
50
agents
0
multimodal
Rankings
| Domain | #Rank | Score | Source |
|---|---|---|---|
| Agentic Capability | 105 | 34.0 | LS |
| Code Ranking | 184 | 69.0 | AA |
| General Ranking | 139 | 62.0 | AA |
| Science | 124 | 70.0 | AA |
Benchmark Scores (LLM Stats)
(LLM Stats (zeroeval))Agents
Toolathlon
46.3%SR
Finance Agent v2
27.9%
Code
MLE-Bench Lite
66.6%SR
MM-ClawBench
62.7%SR
VIBE-Pro
55.6%SR
NL2Repo
39.8%SR
General
Artificial Analysis
50.0%SR
Reasoning
SWE-bench Multilingual
76.5%SR
Terminal-Bench 2.0Stanford × Laude Institute (2026)
57.0%SR
SWE-Bench ProPrinceton NLP (2024)
56.2%SR
Multi-SWE-Bench
52.7%SR
AA Evaluation Indices
(Artificial Analysis)Gpqa(NYU + Cohere + Anthropic (2023))87.4
Tau2(Sierra + U Toronto + Vector Institute (2025))84.8
Lcr(Artificial Analysis)78.3
Ifbench(Google Research (2023))75.7
Terminalbench V2 155.4
Coding Index(Artificial Analysis)52.6
Scicode(UIUC + Argonne National Lab (2024))50.1
Terminalbench Hard(Stanford × Laude Institute (2026))39.4
Hle(Center for AI Safety + Scale AI (2025))29.6
Intelligence Index(Artificial Analysis)22.8
Tau Banking9.9
Terminalbench V4 00.0
LLM Stats Category Scores
(LLM Stats (zeroeval))Code60
Reasoning50
General50
Agents50
Tool Calling50
Finance30
Pricing
Input Price$0.3 / 1M tokens
Output Price$1.2 / 1M tokens
Blended Price (3:1)$0.525 / 1M tokens
Cache Read Price$0.06 / 1M tokens
Cache Write Price$0.375 / 1M tokens
Speed
Tokens/sec0.0
Time to First Token0.00s
Time to Answer0.00s
Provider Price Ranking
Provider Price Ranking
23 providers
Cheapest: MiniMaxMost Expensive: SCX.ai
ProviderInputOutput
1MiniMaxCheapest
$0
$0
2Novita
$0
$0
3Fireworks
$0
$0
4DeepInfra
$0
$0
5EmpirioLabs AI
$0.15
$0.6
6OpenRouter
$0.21
$0.84
7302.AI
$0.3
$1.2
8NovitaAI
$0.3
$1.2
9Kilo Gateway
$0.3
$1.2
10FrogBot
$0.3
$1.2
11Vercel AI Gateway
$0.3
$1.2
12MiniMax (minimax.io)
$0.3
$1.2
13FastRouter
$0.3
$1.2
14MiniMax (minimax.cn)
$0.3
$1.2
15Auriko
$0.3
$1.2
16OrcaRouter
$0.3
$1.2
17Merge Gateway
$0.3
$1.2
18Ofox
$0.3
$1.2
19LLM Gateway
$0.3
$1.2
20ZenMux
$0.3055
$1.2219
21NanoGPT
$0.315
$1.26
22CrossModel
$0.33
$1.32
23SCX.ai
$0.48
$1.79
Compare pricing across different API providers for this model.