de Mistral especializado razonamiento motor engineered con inspectable cadena de pensamiento, matemático proof síntesis, y deliberate decision trees.
Technical Specifications
- Provider
- Mistral AI
- Category
- reasoning
- Release Date
- 2025-03
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- API Pay-as-you-go
- Reasoning Effort Control
- Configurable (Low / Med / High)
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- magistral-medium-latest
- Supported SDK & API Protocol
- Mistral AI REST API (OpenAI-Compatible)
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2027+)
- 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 ($1/1M in) across full 128K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.25/1M 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 Mistral AI Cloud API
- System Card & Safety Framework
- Mistral AI Production Safety & Alignment Verified
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Magistral Medium Cost, Context, Hardware & API Integration
For single-user chat, a $20/mo subscription caps your bill below this API volume.
Break-even point: ~111 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Magistral Medium:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 45.2%
- GPQA Diamond
- 67.8%
- MMLU-Pro
- 82.5%
- HumanEval
- 90%
- Terminal-Bench
- 40%
- AIME
- 76.5%
- Long-Context Reasoning
- 80%
- Chatbot Arena Elo
- 1335pts
Strengths
- Transparent, auditable internal razonamiento trace before final síntesis
- sustancial improvements en competitivo mathematics y algorithmic proofs
- completo 128K ventana de contexto con deliberate herramienta planning
Limitations & Trade-offs
- mayor token salida overhead due un extendido razonamiento traces
- texto-solo entrada sin nativo imagen o video procesamiento
Editorial Assessment
de Mistral answer un el razonamiento de frontera, pairing transparency con rigorous deduction.
Best for: complejo audit reports, legal clause contradiction análisis, y matemático lógica proofs
Compare Magistral Medium
Frequently Asked Questions about Magistral Medium
How much does the Magistral Medium API cost per 1M tokens?+
Magistral Medium by Mistral AI is priced at $1 per 1M input tokens and $3.5 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.25 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Magistral Medium 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 Magistral Medium's context window?+
Magistral Medium features a 128K tokens context window, which equals approximately 96,000 English words or ~256 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 32,768 tokens.
Can I run Magistral Medium locally on my own GPU (Open Weights)?+
No, Magistral Medium is a proprietary closed-weights model hosted by Mistral AI. It cannot be downloaded for local GPU execution and must be accessed via Mistral AI's official API or cloud platform.
Does Mistral AI train on data sent to the Magistral Medium API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (Mistral AI Terms). Full commercial ownership of generated outputs. Supported deployment channels include: Mistral AI Cloud API & Enterprise Endpoints.
How does Magistral Medium perform on coding and reasoning benchmarks?+
Magistral Medium achieves a composite Intelligence Index of 51/100, scoring 45.2% on SWE-bench Verified, 67.8% on GPQA Diamond, 82.5% on MMLU-Pro, and 1335 pts on Chatbot Arena Elo.
What is Magistral Medium best used for?+
Magistral Medium is best suited for: complejo audit reports, legal clause contradiction análisis, y matemático lógica proofs. Assessment: de Mistral answer un el razonamiento de frontera, pairing transparency con rigorous deduction.
Mistral AI Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to Mistral AI's flagship reasoning tier:
Mistral Medium 3.5
Mistral Small 4
Devstral 2
Devstral Medium
Devstral Small
Mistral Small 3.2
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Magistral Medium:
La unidad básica de texto que procesa un modelo de lenguaje, que normalmente equivale a 3 o 4 caracteres o aproximadamente 0,75 palabras. Por ejemplo, una frase típica se divide en varios tokens.
Un conjunto estandarizado de pruebas para evaluar y comparar objetivamente las capacidades de distintos modelos de IA en tareas como programación (SWE-bench) o matemáticas avanzadas (AIME).
La cantidad máxima de tokens que un modelo puede considerar a la vez, incluyendo tanto la entrada que lee como la salida que genera. Una ventana de 1.000.000 de tokens puede procesar unas 750.000 palabras en una sola petición.
Un modelo de IA entrenado para invertir cómputo adicional en pensar y validar hipótesis lógicas antes de responder, diseñado para problemas complejos de ingeniería y matemáticas.
Una técnica de razonamiento paso a paso donde el modelo genera pensamientos intermedios antes de formular la respuesta final, mejorando radicalmente la resolución de problemas matemáticos y lógicos.
La capacidad de un modelo de detectar la necesidad de una función externa y emitir argumentos JSON estructurados para ejecutar API, búsquedas web o consultas a bases de datos.
Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.