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.
İstediğiniz Modelleri Seçin ve Karşılaştırın
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Live comparison: no in-depth editorial review has been published for this pair yet.
Magistral Medium
Derin Akıl Yürütme MotoruMistral AI tarafından geliştirilen Magistral Medium; derin mantıksal akıl yürütme, ileri matematik ve çok adımlı bilimsel analiz için tasarlanmış olup 128K bağlam penceresi, 50 token/sn hız, 51/100 zeka indeksi ve 1M token başına $1/$3.5 fi
$1.00 / 1M
$3.50 / 1M
128K tokens
45.2%
GPT-6 Astra
Yerel Ses ve Konuşma ModeliOpenAI tarafından geliştirilen GPT-6 Astra; doğal ses sentezi, gerçek zamanlı ses işleme ve konuşma metne dönüştürme için tasarlanmış olup 272K bağlam penceresi, 100 token/sn hız, 96/100 zeka indeksi ve 1M token başına $10/$50 fiyatlandırma
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Bir Bakışta Temel Farklar
- 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 |
Hangi Alanda Kim Kazanıyor?
At-a-glance decision frameworkDoğrulanmış Benchmark Puanları
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.
Gecikme Süresi ve Yanıt Hızı
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Gerçek Zamanlı Token Maliyet Simülatörü
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Magistral Medium · Strengths & Key Advantages
- 128K bağlam penceresi ve yanıt başına maksimum 33K çıktı tokenı kapasitesi (SWE-bench Verified 45.2% · GPQA Diamond 67.8%)
- Sadece 850 ms ilk token gecikmesi (TTFT) ile saniyede 50 token yüksek üretim hızı
- İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $1/$3.5 fiyatlandırma)
Considerations & Trade-offs
- Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
- Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir
GPT-6 Astra · Strengths & Key Advantages
- 272K bağlam penceresi ve yanıt başına maksimum 128K çıktı tokenı kapasitesi (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
- Sadece 950 ms ilk token gecikmesi (TTFT) ile saniyede 100 token yüksek üretim hızı
- İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $10/$50 fiyatlandırma)
Considerations & Trade-offs
- Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
- Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir
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 |
Teknik Özellikler
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: Hızlı Yanıtlar (SSS)
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.
Sonuç
Choose Magistral Medium for derin mantıksal akıl yürütme, ileri matematik ve çok adımlı bilimsel analiz, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir., or choose GPT-6 Astra for doğal ses sentezi, gerçek zamanlı ses işleme ve konuşma metne dönüştürme, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir..
Sıkça Sorulan Sorular (SSS)
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.
Related reading
- Aion-3.0 vs Aion-Mini: Benchmark, API Fiyatları ve Hız Karşılaştırması (2026)Karşılaştır
- Aion-3.0 vs Gemini 3.6 Flash: Benchmark, API Fiyatları ve Hız Karşılaştırması (2026)Karşılaştır
- Aion-Mini vs Laguna XS 2.1: Benchmark, API Fiyatları ve Hız Karşılaştırması (2026)Karşılaştır
- Aya Expanse 32B vs Llama 3.2 90B Vision: Benchmark, API Fiyatları ve Hız Karşılaştırması (2026)Karşılaştır
- Aya Expanse 8B vs Command R+: Benchmark, API Fiyatları ve Hız Karşılaştırması (2026)Karşılaştır
- Aya Expanse 8B vs Qwen 2.5 7B Instruct: Benchmark, API Fiyatları ve Hız Karşılaştırması (2026)Karşılaştır
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.
Resmi kaynaklar: Mistral AI & OpenAI Official Documentation