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MiniMax

MiniMax-M2.7-highspeed

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
Modèle phare rapideOfficial Source Verified ↗
82
Intelligence Index

rapide cloud API variant de M2.7 optimisé pour en temps réel agent boucles, interactif code analyse, et élevé-volume d'entreprise pipelines.

Input / Output
$0.25 / $1
per 1M tokens
Context
204K tokens
window
Speed
140
tok/s
Latency
0.29s
TTFT

Technical Specifications

Provider
MiniMax
Category
lightweight
Release Date
2026-03
Knowledge Cutoff
January 2026
Architecture
High-Throughput Hosted Cloud Accelerator
Parameters
Confidential
Context Window
204K tokens
Max Output
8K tokens
Cached Input Price
$0.025 / 1M tokens
Batch API Discount
50% off async batch
Consumer Subscription
API Pay-as-you-go
Reasoning Mode
Yes (Chain-of-Thought)
Reasoning Effort Control
Fixed
Tool Calling
Yes
Structured Outputs
Yes
Open Weights
No (Proprietary Cloud)
Input Modalities
text
Output Modalities
text
Official Documentation
Visit Official Docs ↗

Data Privacy, Licensing & Deployment Governance

API Data Training Policy
API payloads are excluded from model training by default
Model License & Commercial Rights
Proprietary Commercial API (MiniMax Terms)
Deployment & Cloud Availability
MiniMax Cloud API & Enterprise Endpoints
Output Ownership
Full commercial ownership of generated outputs

Official Provider Release Intelligence, API Quotas & Agentic Specs

Compare Multi-Models Side-by-Side →
Official API Model ID (SDK String)
minimax-m2-7-highspeed
Supported SDK & API Protocol
MiniMax REST API (OpenAI-Compatible)
Lifecycle & Deprecation Status
Active GA (Guaranteed support through 2028+)
Production Rate Limits (RPM & TPM)
5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Pricing Tier (>128K / >200K)
Flat rate ($0.25/1M in) across full 204K window
Prompt Cache Write & TTL Policy
Cached input at $0.025/1M tokens
Computer Use & Browser GUI Agent
API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool Calling
Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Code Sandbox
Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Fine-Tuning & Distillation Support
API Prompt Engineering & RAG Distillation
Multimodal Tokenization Billing
Text BPE (~4 chars/token)
Weights Precision & Quantization
Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
Minimum GPU VRAM Requirement
Zero Local VRAM Required (100% Serverless Cloud API)
Supported Inference Engines
Managed MiniMax Cloud API
System Card & Safety Framework
MiniMax Production Safety & Alignment Verified
Enterprise Compliance (SOC2 / HIPAA / ZDR)
SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Engineering & Pricing Workbench

MiniMax-M2.7-highspeed Cost, Context, Hardware & API Integration

500 / day
4,000 tok
1,000 tok
Conversation Depth (History Re-billing):1 Turn (Single-Shot)
50%
Estimated Monthly API Cost (30 Days)
$23.25$30.00
Monthly Savings: $6.75 (Caching/Batch)
Daily Cost:
$0.78
Cost per Request:
$0.00155
Effective Input / 1M:
$0.138
Effective Output / 1M:
$1.000
Subscription ($20/mo) vs API

For single-user chat, a $20/mo subscription caps your bill below this API volume.

Break-even point: ~430 requests/day equals $20/month.

Same Monthly Workload Cost Across Popular Reference Models

MiniMax-M2.7-highspeed (Active)
$23.25
/ month
Gemini 2.5 Flash
$18.00
/ month
DeepSeek V3
$32.70
/ month
GPT-4o
$300.00
/ month
Claude 3.7 Sonnet
$405.00
/ month

Live Prompt Paste Tokenizer & Cost Counter

Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.

Chars / Words
175 / 24
OpenAI o200k
~46 tok
Claude BPE
~49 tok
Llama / DeepSeek
~51 tok

Hybrid Prompt Routing Cascade Simulator

Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to MiniMax-M2.7-highspeed:

Cascaded Monthly Bill:$19.31/mo
Saves $3.94/mo (17% cost reduction) vs sending 100% of traffic to MiniMax-M2.7-highspeed.

Benchmark Scores & 6-Axis Capability Radar

Benchmark Encyclopedia
Coding (89)Reasoning (72)Knowledge (78)Speed (93)Context (85)Cost Value (84)
MiniMax-M2.7-highspeed2026 Frontier Median
GPQA Diamond
63%
MMLU-Pro
78%
HumanEval
89%
Chatbot Arena Elo
1335pts

Strengths

  • 140 tokens/sec diffusion continue velocity avec solid 1335 Arena Elo performances
  • excellent balance entre phare raisonnement et snappy interactif latence
  • abordable hosted tarification ($0.25/1M entrée) avec 204K fenêtre de contexte

Limitations & Trade-offs

  • Slightly inférieur theoretical profondeur que le complet unaccelerated M2.7 modèle
  • propriétaire hosted endpoint rather que à poids ouverts

Editorial Assessment

le ideal production choice pour teams demanding phare-adjacent logique à élevé vitesse.

Best for: élevé-frequency développeur copilots, automatisé ticket triage, et responsive agents

Compare MiniMax-M2.7-highspeed

MiniMax-M2.7-highspeed vs GLM-5-TurboMiniMax-M2.7-highspeed vs MiniMax-M2.5-highspeedMiniMax-M2.7-highspeed vs Gemini 4 ArgonMiniMax-M2.7-highspeed vs GPT-6 AstraMiniMax-M2.7-highspeed vs Claude Opus 5.5MiniMax-M2.7-highspeed vs GPT-6.1 Sol

Frequently Asked Questions about MiniMax-M2.7-highspeed

How much does the MiniMax-M2.7-highspeed API cost per 1M tokens?+

MiniMax-M2.7-highspeed by MiniMax is priced at $0.25 per 1M input tokens and $1 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.025 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.

Should I use a $20/month subscription or the MiniMax-M2.7-highspeed pay-as-you-go API?+

A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.

How many words and pages fit in MiniMax-M2.7-highspeed's context window?+

MiniMax-M2.7-highspeed features a 204K tokens context window, which equals approximately 153,000 English words or ~408 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 8,192 tokens.

Can I run MiniMax-M2.7-highspeed locally on my own GPU (Open Weights)?+

No, MiniMax-M2.7-highspeed is a proprietary closed-weights model hosted by MiniMax. It cannot be downloaded for local GPU execution and must be accessed via MiniMax's official API or cloud platform.

Does MiniMax train on data sent to the MiniMax-M2.7-highspeed API, and is commercial use allowed?+

API payloads are excluded from model training by default. License tier: Proprietary Commercial API (MiniMax Terms). Full commercial ownership of generated outputs. Supported deployment channels include: MiniMax Cloud API & Enterprise Endpoints.

How does MiniMax-M2.7-highspeed perform on coding and reasoning benchmarks?+

MiniMax-M2.7-highspeed achieves a composite Intelligence Index of 82/100, scoring N/A% on SWE-bench Verified, 63% on GPQA Diamond, 78% on MMLU-Pro, and 1335 pts on Chatbot Arena Elo.

What is MiniMax-M2.7-highspeed best used for?+

MiniMax-M2.7-highspeed is best suited for: élevé-frequency développeur copilots, automatisé ticket triage, et responsive agents. Assessment: le ideal production choice pour teams demanding phare-adjacent logique à élevé vitesse.

MiniMax Family Lineage, Routing Tiers & Upgrade Path

Step down to a lighter sibling for high-volume routing or step up to MiniMax's flagship reasoning tier:

Fast Router / Budget Tier2026-06

MiniMax-M3

$0 / $0 · 524K tokensIQ 89
Fast Router / Budget Tier2026-03

MiniMax-M2.7

$0 / $0 · 204K tokensIQ 85
Fast Router / Budget Tier2026-02

MiniMax-M2.5

$0 / $0 · 204K tokensIQ 82
Sibling Production Tier2026-02

MiniMax-M2.5-highspeed

$0.15 / $0.6 · 204K tokensIQ 78
Fast Router / Budget Tier2025-12

MiniMax-M2.1

$0 / $0 · 204K tokensIQ 80
Fast Router / Budget Tier2025-10

MiniMax-M2

$0 / $0 · 196K tokensIQ 78

AI Glossary & Architecture Concepts

View full glossary →

Key machine learning concepts and benchmarks relevant to MiniMax-M2.7-highspeed:

Jeton (Token)

L'unité textuelle de base traitée par un modèle linguistique, représentant généralement 3 à 4 caractères ou environ 0,75 mot. Par exemple, une phrase courante est découpée en plusieurs jetons.

Benchmark (Banc d’essai)

Une suite de tests standardisés permettant d'évaluer et de comparer objectivement les performances des modèles d'IA sur des tâches ciblées (code avec SWE-bench, mathématiques avec AIME, etc.).

Fenêtre de contexte

Le nombre maximal de jetons qu'un modèle peut traiter simultanément (entrée et sortie comprises). Une fenêtre de 1 000 000 jetons permet d'analyser environ 750 000 mots en une seule requête.

Modèle de raisonnement

Un modèle d'IA entraîné par apprentissage par renforcement pour allouer du temps de calcul à la réflexion logique avant d'émettre une solution, idéal pour les problèmes scientifiques et le code complexe.

Chaîne de pensée (CoT)

Une méthode de raisonnement pas-à-pas où le modèle décompose le problème en étapes logiques intermédiaires avant de conclure, augmentant drastiquement la précision en mathématiques et programmation.

Appel d'outils (Tool Calling)

La capacité d'un LLM à déterminer quand une action externe est requise et à générer des arguments structurés pour invoquer des API, calculatrices ou bases de données avant de poursuivre.

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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: MiniMax API Documentation↗