Head-to-Head Model Comparison

Mistral Medium 3 vs Mistral Small 3

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial

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Mistral Medium 3Profile

Mistral Small 3Profile

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Mistral AI

Mistral Medium 3

Modelo Base de Pesos Abiertos

Mistral Medium 3 de Mistral AI es un modelo de IA diseñado para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, con ventana de contexto de 131K, velocidad de 85 tokens/s, índice de inteligencia de 47/1

Intelligence Index47 / 100

Input Token:

$0.40 / 1M

Output Token:

$2.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

40.5%

Mistral AI

Mistral Small 3

Modelo Base de Pesos Abiertos

Mistral Small 3 de Mistral AI es un modelo de IA diseñado para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, con ventana de contexto de 32K, velocidad de 105 tokens/s, índice de inteligencia de 41/10

Intelligence Index41 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.30 / 1M

Context Window:

32K tokens

SWE-bench Verified:

31.5%

Diferencias Clave de un Vistazo

Mistral Small 3 is 5.2x cheaper for API usage (input + output tokens combined).
Mistral Medium 3 has a larger context window (131K vs 32K tokens).
Mistral Small 3 is faster at 105 tok/s vs 85 tok/s.
Mistral Medium 3 leads on SWE-bench coding (40.5% vs 31.5%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Característica	Mistral Medium 3	Mistral Small 3
Intelligence Index Composite reasoning & knowledge score (0-100)	47	41
Provider	Mistral AI	Mistral AI
Input Price Cost per million input tokens	$0.40 / 1M	$0.10 / 1M
Output Price Cost per million output tokens	$2.00 / 1M	$0.30 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.35 / 1M	$0.09 / 1M
Context Window Maximum input + output tokens	131.1K tokens~197 A4 pages of text	32K tokens~48 A4 pages of text
Max Output Tokens Per single request	16K	8K
Throughput Speed Tokens generated per second	85 tok/s	105 tok/s
SWE-bench Verified Real-world software engineering	40.5%	31.5%
GPQA Diamond Graduate-level reasoning	57.5%	46.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.10 / 1M	$0.05 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

Mistral Medium 3

+9.0% SWE-bench lead

Costo

Mistral Small 3

5.2x cheaper monthly runtime

Velocidad

Mistral Small 3

+24% faster generation

Contexto

Mistral Medium 3

131.1K tokens window

Puntuaciones de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

Mistral Medium 3Mistral Small 3

SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

40.5%vs31.5%

GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

57.5%vs46.5%

MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

79.5%vs70.2%

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1310ptsvs1238pts

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

36%vs27%

AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

68%vs52%

Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

77%vs64%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs105 tok/s

Latencia y Tiempo de Respuesta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

Mistral Medium 30.48s

Mistral Small 30.38s

Est. End-to-End Response (500 tokens)TTFT + generation time

Mistral Medium 36.36s

Mistral Small 35.14s

Simulador Interactivo de Costos de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Mistral Medium 3 Monthly API Bill

$2.55 / month

$0.4/1M in · $2/1M out

Mistral Small 3 Monthly API Bill

$0.50 / month

$0.1/1M in · $0.3/1M out

Mistral Small 3 saves approximately $2.06 / month (81%) under this workload.5.2x Savings

Mistral Medium 3 · Strengths & Key Advantages

Ventana de contexto de 131K con hasta 16K tokens de salida máxima (SWE-bench Verified 40.5% · GPQA Diamond 57.5%)
Rendimiento ágil de 85 tokens/segundo con latencia inicial (TTFT) de solo 480 ms
Pesos abiertos (Confidential (~70B)) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama

Considerations & Trade-offs

Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Mistral Small 3 · Strengths & Key Advantages

Ventana de contexto de 32K con hasta 8K tokens de salida máxima (SWE-bench Verified 31.5% · GPQA Diamond 46.5%)
Rendimiento ágil de 105 tokens/segundo con latencia inicial (TTFT) de solo 380 ms
Pesos abiertos (24B) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama

Considerations & Trade-offs

Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	Mistral Medium 3	Mistral Small 3
Cost per Task Estimated USD to finish one task	$0.35	$0.08
Output Tokens / Task Tokens generated per task	35K	25K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	Mistral Medium 3	Mistral Small 3
Official API Model ID (SDK)	mistral-medium-3-latest	mistral-small-3-latest
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-05	2025-01
Knowledge Cutoff	March 2025	December 2024
Architecture	Enterprise Multimodal Transformer	Compact Dense Transformer
Parameters	Confidential (~70B)	24B
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Flat rate ($0.4/1M in) across full 131K window	Flat rate ($0.1/1M in) across full 32K window
Prompt Cache Policy & TTL	Cached input at $0.1/1M tokens	Cached input at $0.05/1M tokens
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	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	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools	Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning Support	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 15 GB VRAM (4-bit Quantized) · 52 GB VRAM (Native BF16)
Safety & Frontier Classification	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text, vision	text
Output Modalities	text	text

Mistral Medium 3 vs Mistral Small 3: Respuestas Rápidas (FAQ)

Which is more intelligent, Mistral Medium 3 or Mistral Small 3?

Mistral Medium 3 is more intelligent. It scores 47 compared with 41 on the composite Intelligence Index.

Which model is faster?

Mistral Small 3 is faster, generating 105 tokens per second compared with 85 tokens per second.

Which model is cheaper to run?

Mistral Small 3 is cheaper at $0.09 per 1M tokens blended, compared with $0.35 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Mistral Small 3 has lower latency, with a time to first token of 0.38s compared with 0.48s.

Which model has a larger context window?

Mistral Medium 3 has a larger context window, supporting 131.1K tokens compared with 32K tokens.

Veredicto

Tanto Mistral Medium 3 (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) como Mistral Small 3 (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) destacan en producción: Mistral Medium 3 lidera en inteligencia general y programación, Mistral Small 3 ofrece mayor velocidad de generación de tokens y Mistral Small 3 resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Mistral Medium 3 o Mistral Small 3?+

En las pruebas de inteligencia compuesta y resolución de código, Mistral Medium 3 obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Mistral Medium 3 frente a Mistral Small 3?+

Mistral Medium 3 cuesta $0.40 / $2.00 por millón de tokens de entrada/salida, mientras que Mistral Small 3 cuesta $0.10 / $0.30. En costo combinado, Mistral Small 3 es la opción más económica.

¿Qué modelo tiene mayor ventana de contexto y menor latencia?+

Mistral Medium 3 cuenta con 131.1K tokens de contexto frente a 32K tokens de Mistral Small 3. En velocidad de inferencia, Mistral Small 3 ofrece un rendimiento superior.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Mistral Medium 3 vs Mistral Small 3

Cambia y Compara Cualquier Modelo

Mistral Medium 3

Mistral Small 3

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Mistral Medium 3 · Strengths & Key Advantages

Considerations & Trade-offs

Mistral Small 3 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

Mistral Medium 3 vs Mistral Small 3: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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