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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

24
general
52
coding
87
reasoning
63
science
50
agents
0
multimodal

Classements

Domaine#RangScoreSource
Capacité agentique103
34.0
LS
Classement codage181
69.0
AA
Classement général138
62.0
AA
Science122
70.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

Toolathlon46.3%Aut.
Finance Agent v227.9%

Code

MLE-Bench Lite66.6%Aut.
MM-ClawBench62.7%Aut.
VIBE-Pro55.6%Aut.
NL2Repo39.8%Aut.

General

Artificial Analysis50.0%Aut.

Reasoning

SWE-bench Multilingual76.5%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)57.0%Aut.
SWE-Bench ProPrinceton NLP (2024)56.2%Aut.
Multi-SWE-Bench52.7%Aut.

Indices d'évaluation AA

(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 1
55.4
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 Banking
9.9

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

23 fournisseurs

Moins cher: MiniMaxPlus cher: SCX.ai
FournisseurEntréeSortie
1MiniMaxMoins cher
$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

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes