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MiniMax-M2.7

MiniMaxMiniMaxOpen WeightMIT · Usage Commercial

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.

Date de sortie
2026-03-18
Paramètres
Longueur du contexte
205K
Modalités
text

Radar de capacités

37
general
52
coding
87
reasoning
62
science
50
agents
0
multimodal

Classements

Domaine#RangScoreSource
Capacité agentique127
34.0
LS
Classement codage106
71.0
AA
Classement général81
74.0
AA
Science80
74.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

MLE-Bench Lite66.6%Aut.
MM-ClawBench62.7%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)57.0%Aut.
SWE-Bench ProPrinceton NLP (2024)56.2%Aut.
VIBE-Pro55.6%Aut.
Toolathlon46.3%Aut.
NL2Repo39.8%Aut.
Finance Agent v227.9%

Code

SWE-bench Multilingual76.5%Aut.
Multi-SWE-Bench52.7%Aut.

General

Artificial Analysis50.0%Aut.

Indices d'évaluation AA

(Artificial Analysis)
Coding Index(Artificial Analysis)
52.6
Intelligence Index(Artificial Analysis)
38.9
Gpqa(NYU + Cohere + Anthropic (2023))
0.9
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.8
Ifbench(Google Research (2023))
0.8
Lcr(Artificial Analysis)
0.8
Terminalbench V2 1
0.6
Scicode(UIUC + Argonne National Lab (2024))
0.5
Terminalbench Hard(Stanford × Laude Institute (2026))
0.4
Hle(Center for AI Safety + Scale AI (2025))
0.3
Tau Banking
0.1

Scores par catégorie LLM Stats

(LLM Stats (zeroeval))
Code
60
Reasoning
50
General
50
Agents
50
Tool Calling
50
Finance
30

Tarification

Prix d'entrée$0.3 / 1M tokens
Prix de sortie$1.2 / 1M tokens
Prix mixte (3:1)$0.525 / 1M tokens
Prix de lecture cache$0.06 / 1M tokens
Prix d'écriture cache$0.375 / 1M tokens

Vitesse

Tokens/sec0.0
Délai du premier token0.00s
Temps de réponse0.00s

Classement des Prix par Fournisseur

Classement des Prix par Fournisseur

20 fournisseurs

Moins cher: MiniMaxPlus cher: SCX.ai
FournisseurEntréeSortie
1MiniMaxMoins cher
$0
$0
2Fireworks
$0
$0
3Novita
$0
$0
4EmpirioLabs AI
$0.15
$0.6
5302.AI
$0.3
$1.2
6OpenRouter
$0.3
$1.2
7NovitaAI
$0.3
$1.2
8Kilo Gateway
$0.3
$1.2
9FrogBot
$0.3
$1.2
10Vercel AI Gateway
$0.3
$1.2
11MiniMax (minimax.io)
$0.3
$1.2
12FastRouter
$0.3
$1.2
13MiniMax (minimaxi.com)
$0.3
$1.2
14Auriko
$0.3
$1.2
15OrcaRouter
$0.3
$1.2
16Merge Gateway
$0.3
$1.2
17ZenMux
$0.3055
$1.2219
18NanoGPT
$0.315
$1.26
19CrossModel
$0.33
$1.32
20SCX.ai
$0.48
$1.79

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes