Magistral Medium vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Magistral Medium by Mistral AI against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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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%
GPT-6 Astra
Model Suara & Audio AsliGPT-6 Astra dari OpenAI adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 272K, kecepatan 100 token/detik, indeks kecerdasan 96/100, serta tarif $10/$
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Perbedaan Utama Sekilas
- Magistral Medium is 12.2x cheaper for API usage (input + output tokens combined).
- GPT-6 Astra has a larger context window (272K vs 128K tokens).
- GPT-6 Astra is faster at 100 tok/s vs 50 tok/s.
- GPT-6 Astra leads on SWE-bench coding (82.4% vs 45.2%).
| Feature | Magistral Medium | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 51 | 96 |
Provider | Mistral AI | OpenAI |
Input Price Cost per million input tokens | $1.00 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $3.50 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.72 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 33K | 128K |
Throughput Speed Tokens generated per second | 50 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | 45.2% | 82.4% |
GPQA Diamond Graduate-level reasoning | 67.8% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.25 / 1M | $1.00 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor 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.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
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
GPT-6 Astra · Strengths & Key Advantages
- Jendela konteks 272K dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
- Kecepatan generasi tinggi 100 token/detik dengan latensi token pertama (TTFT) hanya 950 ms
- Skema harga API kompetitif (tarif $10/$50 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
- Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Magistral Medium | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.65 | $2.15 |
Output Tokens / Task Tokens generated per task | 40K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 32K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Magistral Medium | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | magistral-medium-latest | gpt-6-astra |
| API Protocol | Mistral AI REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-03 | 2026-09 |
| Knowledge Cutoff | January 2025 | June 2026 |
| Architecture | Reinforcement-Learned Reasoning Transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | Confidential (~70B) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($1/1M in) across full 128K window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.25/1M tokens | Automatic prefix caching at $1/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| 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 | OpenAI Preparedness Framework Audited & System Card Published |
| 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, audio |
Magistral Medium vs GPT-6 Astra: Jawaban Cepat (FAQ)
Which is more intelligent, Magistral Medium or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 51 on the composite Intelligence Index.
Which model is faster?
GPT-6 Astra is faster, generating 100 tokens per second compared with 50 tokens per second.
Which model is cheaper to run?
Magistral Medium is cheaper at $0.72 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Magistral Medium has lower latency, with a time to first token of 0.85s compared with 0.95s.
Which model has a larger context window?
GPT-6 Astra has a larger context window, supporting 272K tokens compared with 128K tokens.
Kesimpulan
Choose Magistral Medium for sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem rag perusahaan, dan integrasi api skala produksi., or choose GPT-6 Astra for sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem rag perusahaan, dan integrasi api skala produksi..
Pertanyaan Umum (FAQ)
Which is cheaper: Magistral Medium or GPT-6 Astra?+
Magistral Medium costs $1/1M input and $3.5/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Magistral Medium or GPT-6 Astra?+
Magistral Medium supports 128K tokens whereas GPT-6 Astra supports 272K tokens.
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: Mistral AI & OpenAI Official Documentation