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Head-to-Head Model Comparison

Magistral Medium vs ERNIE 4.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期：October 2026编辑政策
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Magistral Medium vs ERNIE 4.5: Benchmarks, Pricing & Speed Comparison

Mistral AI 的 Magistral Medium 与 Baidu 的 ERNIE 4.5 是当前备受关注的两款主力 AI 模型。Magistral Medium 提供 128K Token 上下文窗口，API 定价为每百万 Token 输入 $1.00 / 输出 $3.50；而 ERNIE 4.5 提供 128K Token 上下文窗口，定价为每百万 Token 输入 $0.60 / 输出 $2.40。以下为两者的基准测试、延迟与成本全面对比。

模型直接对比 (VS)

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Mistral AI

Magistral Medium

深度逻辑推理引擎

Mistral AI 推出的 Magistral Medium 是一款专为博士级数理逻辑、科学推导与多步思维链 (CoT) 设计的深度推理大模型，具备 128K 上下文窗口、50 Token/秒生成速度与 51/100 综合智能指数（每百万 Token $1 输入 / $3.5 输出）。

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

旗舰前沿大模型

Baidu 推出的 ERNIE 4.5 是一款面向复杂企业级推理、软件开发与全场景生产工作流的旗舰前沿大模型，具备 128K 上下文窗口、75 Token/秒生成速度与 81/100 综合智能指数（每百万 Token $0.6 输入 / $2.4 输出）。

Intelligence Index81 / 100
Input Token:

$0.60 / 1M

Output Token:

$2.40 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

核心差异一览

  • 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 →
FeatureMagistral MediumERNIE 4.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5181
Provider
Mistral AIBaidu
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 text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
33K8K
Throughput Speed
Tokens generated per second
50 tok/s75 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

各项指标谁更胜一筹？

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

权威基准测试得分对比

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

延迟与响应速度

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

实时 Token 成本模拟器

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

100K / day
10K500K1M
30K / day
5K150K300K
50% 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

  • 提供 128K 上下文窗口与最高 33K 输出容量，核心基准表现优异（SWE-bench Verified 45.2% · GPQA Diamond 67.8%）
  • 高达 50 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 850 毫秒
  • 极具竞争力的 API 定价（每百万 Token $1 输入 / $3.5 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
  • 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
  • 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型

ERNIE 4.5 · Strengths & Key Advantages

  • 提供 128K 上下文窗口与最高 8K 输出容量，核心基准表现优异（GPQA Diamond 60% · MMLU-Pro 78.5%）
  • 高达 75 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 510 毫秒
  • 极具竞争力的 API 定价（每百万 Token $0.6 输入 / $2.4 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
  • 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
  • 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型

Token Use & Task Economics

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

MetricMagistral MediumERNIE 4.5
Cost per Task
Estimated USD to finish one task
$0.65$0.16
Output Tokens / Task
Tokens generated per task
40K18K
Reasoning Tokens / Task
Thinking tokens burned per task
22K4K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureMagistral MediumERNIE 4.5
Official API Model ID (SDK)magistral-medium-latesternie-4-5
API ProtocolMistral AI REST API (OpenAI-Compatible)Baidu REST API (OpenAI-Compatible)
Release Date2025-032025-03
Knowledge CutoffJanuary 2025December 2024
ArchitectureReinforcement-Learned Reasoning TransformerMultimodal Foundation Knowledge Transformer
ParametersConfidential (~70B)Confidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($1/1M in) across full 128K windowFlat rate ($0.6/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.25/1M tokensCached input at $0.06/1M tokens
Computer Use / GUI AgentAPI / 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 CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAMCloud-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 ClassificationMistral AI Production Safety & Alignment VerifiedBaidu Production Safety & Alignment Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision, audio
Output Modalitiestexttext

Magistral Medium vs ERNIE 4.5: 常见问题解答 (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.

综合结论

综合来看，Magistral Medium（适合：专为博士级数理逻辑、科学推导与多步思维链 (CoT) 设计的深度推理任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）与 ERNIE 4.5（适合：面向复杂企业级推理、软件开发与全场景生产工作流的旗舰前沿任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）各具优势：ERNIE 4.5 在综合智能与编程基准测试中表现更强，ERNIE 4.5 拥有更快的 Token 生成速度，而 ERNIE 4.5 则在规模化 API 部署中具备更高的成本效益。

常见问题 (FAQ)

在编程和深度推理方面，Magistral Medium 和 ERNIE 4.5 哪个更强？+

在综合智能指数与编程基准评测中，ERNIE 4.5 表现占优。建议结合上方的 SWE-bench Verified 与 GPQA Diamond 跑分根据具体场景选择。

Magistral Medium 与 ERNIE 4.5 的 API 价格哪个更便宜？+

Magistral Medium 的 API 价格为输入 $1.00 / 输出 $3.50（每百万 Token），ERNIE 4.5 为输入 $0.60 / 输出 $2.40。综合混合成本来看，ERNIE 4.5 更具性价比。

哪款模型拥有更大的上下文窗口和更快的响应速度？+

Magistral Medium 支持 128K Token 上下文窗口，而 ERNIE 4.5 支持 128K Token。在流式生成速度方面，ERNIE 4.5 的吞吐表现更快。

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 & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

数据来源: Mistral AI 与 Baidu 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。