Head-to-Head Model Comparison

Magistral Medium vs ERNIE 4.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

Cambia e Confronta Qualsiasi Modello

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Magistral MediumProfile

ERNIE 4.5Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Mistral AI

Magistral Medium

Motore di Ragionamento Profondo

Magistral Medium di Mistral AI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 128K, velocità di 50 token/s, indice di intelligenza di 51/100 e t

Intelligence Index51 / 100

Input Token:

$1.00 / 1M

Output Token:

$3.50 / 1M

Context Window:

128K tokens

SWE-bench Verified:

45.2%

Baidu

ERNIE 4.5

Modello Ammiraglia di Frontiera

ERNIE 4.5 di Baidu è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 128K, velocità di 75 token/s, indice di intelligenza di 81/100 e

Intelligence Index81 / 100

Input Token:

$0.60 / 1M

Output Token:

$2.40 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Differenze Chiave a Colpo d’Occhio

ERNIE 4.5 is 1.6x cheaper for API usage (input + output tokens combined).
ERNIE 4.5 is faster at 75 tok/s vs 50 tok/s.

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

Feature	Magistral Medium	ERNIE 4.5
Intelligence Index Composite reasoning & knowledge score (0-100)	51	81
Provider	Mistral AI	Baidu
Input Price Cost per million input tokens	$1.00 / 1M	$0.60 / 1M
Output Price Cost per million output tokens	$3.50 / 1M	$2.40 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.72 / 1M	$0.40 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	33K	8K
Throughput Speed Tokens generated per second	50 tok/s	75 tok/s
SWE-bench Verified Real-world software engineering	45.2%	N/A
GPQA Diamond Graduate-level reasoning	67.8%	60%
Cached Input Price Prompt caching discount per 1M tokens	$0.25 / 1M	$0.06 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

ERNIE 4.5

1.6x cheaper monthly runtime

Speed

ERNIE 4.5

+50% faster generation

Context

Tied

128K tokens window

Punteggi Benchmark Verificati

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

Magistral MediumERNIE 4.5

SWE-bench Verified (Autonomous Coding)

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

45.2%vsN/A

GPQA Diamond (Doctorate-Level Science & Math)

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

67.8%vs60%

MMLU-Pro (Multi-task Language Understanding)

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

82.5%vs78.5%

LMSYS Chatbot Arena Elo

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

1335ptsvs1325pts

Terminal-Bench (Agentic Coding & Terminal Use)

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

40%vsN/A

AIME (Advanced Math Competition)

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

76.5%vsN/A

Long-Context Reasoning

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

80%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

50 tok/s vs75 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

Magistral Medium0.85s

ERNIE 4.50.51s

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

Magistral Medium10.85s

ERNIE 4.57.18s

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)

Magistral Medium Monthly API Bill

$5.03 / month

$1/1M in · $3.5/1M out

ERNIE 4.5 Monthly API Bill

$3.15 / month

$0.6/1M in · $2.4/1M out

ERNIE 4.5 saves approximately $1.88 / month (37%) under this workload.1.6x Savings

Magistral Medium · Strengths & Key Advantages

Finestra di contesto da 128K con capacità massima di output fino a 33K token (SWE-bench Verified 45.2% · GPQA Diamond 67.8%)
Throughput elevato di 50 token/secondo con latenza al primo token (TTFT) di soli 850 ms
Economia API competitiva ($1/$3.5 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

ERNIE 4.5 · Strengths & Key Advantages

Finestra di contesto da 128K con capacità massima di output fino a 8K token (GPQA Diamond 60% · MMLU-Pro 78.5%)
Throughput elevato di 75 token/secondo con latenza al primo token (TTFT) di soli 510 ms
Economia API competitiva ($0.6/$2.4 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
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	Magistral Medium	ERNIE 4.5
Cost per Task Estimated USD to finish one task	$0.65	$0.16
Output Tokens / Task Tokens generated per task	40K	18K
Reasoning Tokens / Task Thinking tokens burned per task	22K	4K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Magistral Medium	ERNIE 4.5
Official API Model ID (SDK)	magistral-medium-latest	ernie-4-5
API Protocol	Mistral AI REST API (OpenAI-Compatible)	Baidu REST API (OpenAI-Compatible)
Release Date	2025-03	2025-03
Knowledge Cutoff	January 2025	December 2024
Architecture	Reinforcement-Learned Reasoning Transformer	Multimodal Foundation Knowledge Transformer
Parameters	Confidential (~70B)	Confidential
Enterprise Rate Limits (RPM / TPM)	5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM	5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($1/1M in) across full 128K window	Flat rate ($0.6/1M in) across full 128K window
Prompt Cache Policy & TTL	Cached input at $0.25/1M tokens	Cached input at $0.06/1M 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	API Prompt Engineering & RAG Distillation	API Prompt Engineering & RAG Distillation
Multimodal Token Billing	Text BPE (~4 chars/token)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	Mistral AI Production Safety & Alignment Verified	Baidu Production Safety & Alignment Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text	text, vision, audio
Output Modalities	text	text

Magistral Medium vs ERNIE 4.5: Risposte Rapide (FAQ)

Which is more intelligent, Magistral Medium or ERNIE 4.5?

ERNIE 4.5 is more intelligent. It scores 81 compared with 51 on the composite Intelligence Index.

Which model is faster?

ERNIE 4.5 is faster, generating 75 tokens per second compared with 50 tokens per second.

Which model is cheaper to run?

ERNIE 4.5 is cheaper at $0.40 per 1M tokens blended, compared with $0.72 (7:2:1 cache:input:output ratio).

Which model has lower latency?

ERNIE 4.5 has lower latency, with a time to first token of 0.51s compared with 0.85s.

Verdetto

Sia Magistral Medium (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) sia ERNIE 4.5 (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: ERNIE 4.5 guida nei benchmark di ragionamento e programmazione, ERNIE 4.5 garantisce una generazione più rapida e ERNIE 4.5 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Magistral Medium o ERNIE 4.5?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale ERNIE 4.5. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Magistral Medium e ERNIE 4.5?+

Magistral Medium costa $1.00 / $3.50 per milione di token di input/output, mentre ERNIE 4.5 costa $0.60 / $2.40. Nel costo combinato, ERNIE 4.5 risulta più economico.

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

Magistral Medium supporta 128K token di contesto contro 128K token di ERNIE 4.5, mentre ERNIE 4.5 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)

Magistral Medium vs ERNIE 4.5

Cambia e Confronta Qualsiasi Modello

Magistral Medium

ERNIE 4.5

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Magistral Medium · Strengths & Key Advantages

Considerations & Trade-offs

ERNIE 4.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Magistral Medium vs ERNIE 4.5: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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