Head-to-Head Model Comparison

Mistral Medium 3 vs Mistral Small 3

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale

Cambia e Confronta Qualsiasi Modello

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Mistral Medium 3Profile

Mistral Small 3Profile

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Mistral AI

Mistral Medium 3

Modello Base a Pesi Aperti

Mistral Medium 3 di Mistral AI è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 131K, velocità di 85 token/s, indice di intelligenza di 47

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

Modello Base a Pesi Aperti

Mistral Small 3 di Mistral AI è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 32K, velocità di 105 token/s, indice di intelligenza di 41/

Intelligence Index41 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.30 / 1M

Context Window:

32K tokens

SWE-bench Verified:

31.5%

Differenze Chiave a Colpo d’Occhio

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 →

Feature	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

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Mistral Medium 3

+9.0% SWE-bench lead

Cost

Mistral Small 3

5.2x cheaper monthly runtime

Speed

Mistral Small 3

+24% faster generation

Context

Mistral Medium 3

131.1K tokens window

Punteggi Benchmark Verificati

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

Latenza e Tempo di Risposta

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

Simulatore Interattivo dei Costi Token

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

Finestra di contesto da 131K con capacità massima di output fino a 16K token (SWE-bench Verified 40.5% · GPQA Diamond 57.5%)
Throughput elevato di 85 token/secondo con latenza al primo token (TTFT) di soli 480 ms
Pesi aperti (Confidential (~70B)) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama

Considerations & Trade-offs

Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Mistral Small 3 · Strengths & Key Advantages

Finestra di contesto da 32K con capacità massima di output fino a 8K token (SWE-bench Verified 31.5% · GPQA Diamond 46.5%)
Throughput elevato di 105 token/secondo con latenza al primo token (TTFT) di soli 380 ms
Pesi aperti (24B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama

Considerations & Trade-offs

Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

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

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	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: Risposte Rapide (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.

Verdetto

Sia Mistral Medium 3 (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) sia Mistral Small 3 (Ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Mistral Medium 3 guida nei benchmark di ragionamento e programmazione, Mistral Small 3 garantisce una generazione più rapida e Mistral Small 3 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Mistral Medium 3 o Mistral Small 3?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Mistral Medium 3. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Mistral Medium 3 e Mistral Small 3?+

Mistral Medium 3 costa $0.40 / $2.00 per milione di token di input/output, mentre Mistral Small 3 costa $0.10 / $0.30. Nel costo combinato, Mistral Small 3 risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

Mistral Medium 3 supporta 131.1K token di contesto contro 32K token di Mistral Small 3, mentre Mistral Small 3 offre una velocità di generazione superiore.

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 e Confronta Qualsiasi Modello

Mistral Medium 3

Mistral Small 3

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Mistral Medium 3 · Strengths & Key Advantages

Considerations & Trade-offs

Mistral Small 3 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Mistral Medium 3 vs Mistral Small 3: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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