Magistral Medium vs ERNIE 4.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Magistral Medium dari Mistral AI dan ERNIE 4.5 dari Baidu adalah dua model AI unggulan. Magistral Medium menawarkan jendela konteks 128K token dengan harga $1.00/$3.50 per 1 juta token, sedangkan ERNIE 4.5 menyediakan konteks 128K token seharga $0.60/$2.40 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Magistral Medium
Mesin Penalaran MendalamMagistral Medium dari Mistral AI adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 128K, kecepatan 50 token/detik, indeks kecerdasan 51/100, serta tar
$1.00 / 1M
$3.50 / 1M
128K tokens
45.2%
ERNIE 4.5
Model Unggulan Garis DepanERNIE 4.5 dari Baidu adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 128K, kecepatan 75 token/detik, indeks kecerdasan 81/100, serta tarif $0.6
$0.60 / 1M
$2.40 / 1M
128K tokens
N/A
Perbedaan Utama Sekilas
- 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.
| 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 |
Siapa Unggul di Mana?
At-a-glance decision frameworkEvaluations ongoing
Skor Benchmark Terverifikasi
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Magistral Medium · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 33K token (SWE-bench Verified 45.2% · GPQA Diamond 67.8%)
- Kecepatan generasi tinggi 50 token/detik dengan latensi token pertama (TTFT) hanya 850 ms
- Skema harga API kompetitif (tarif $1/$3.5 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
- Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
ERNIE 4.5 · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 8K token (GPQA Diamond 60% · MMLU-Pro 78.5%)
- Kecepatan generasi tinggi 75 token/detik dengan latensi token pertama (TTFT) hanya 510 ms
- Skema harga API kompetitif (tarif $0.6/$2.4 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
- Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
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 |
Spesifikasi Teknis
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: Jawaban Cepat (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.
Kesimpulan
Baik Magistral Medium (Sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun ERNIE 4.5 (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: ERNIE 4.5 unggul dalam penalaran dan pemrograman, ERNIE 4.5 memberikan kecepatan generasi token lebih tinggi, dan ERNIE 4.5 lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Magistral Medium atau ERNIE 4.5?+
Dalam indeks kecerdasan gabungan dan benchmark coding, ERNIE 4.5 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Magistral Medium vs ERNIE 4.5?+
Magistral Medium mengenakan biaya $1.00 / $3.50 per 1M token input/output, sedangkan ERNIE 4.5 sebesar $0.60 / $2.40. Secara keseluruhan, ERNIE 4.5 lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Magistral Medium mendukung konteks 128K token dibandingkan 128K token pada ERNIE 4.5, sementara ERNIE 4.5 unggul dalam kecepatan output token per detik.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
Sumber resmi: Dokumentasi API resmi Mistral AI & Baidu serta evaluasi benchmark independen (2026).