GPT-6 Astra vs Qwen3.7 Max
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare GPT-6 Astra by OpenAI against Qwen3.7 Max by Alibaba across real-world coding, reasoning, token economics, and latency.
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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%
Qwen3.7 Max
Otonom Ajan ve Araç ModeliAlibaba tarafından geliştirilen Qwen3.7 Max; otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon için tasarlanmış olup 1M bağlam penceresi, 80 token/sn hız, 92/100 zeka indeksi ve 1M token başına $1.8/$7.2 fiyatland
$1.80 / 1M
$7.20 / 1M
1M tokens
73.5%
Bir Bakışta Temel Farklar
- Qwen3.7 Max is 6.5x cheaper for API usage (input + output tokens combined).
- Qwen3.7 Max has a larger context window (1M vs 272K tokens).
- GPT-6 Astra is faster at 100 tok/s vs 80 tok/s.
- GPT-6 Astra leads on SWE-bench coding (82.4% vs 73.5%).
| Feature | GPT-6 Astra | Qwen3.7 Max |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 96 | 92 |
Provider | OpenAI | Alibaba |
Input Price Cost per million input tokens | $10.00 / 1M | $1.80 / 1M |
Output Price Cost per million output tokens | $50.00 / 1M | $7.20 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $7.70 / 1M | $1.21 / 1M |
Context Window Maximum input + output tokens | 272K tokens~408 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 128K | 32K |
Throughput Speed Tokens generated per second | 100 tok/s | 80 tok/s |
SWE-bench Verified Real-world software engineering | 82.4% | 73.5% |
GPQA Diamond Graduate-level reasoning | 80.9% | 78.5% |
Cached Input Price Prompt caching discount per 1M tokens | $1.00 / 1M | $0.18 / 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.
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
Qwen3.7 Max · Strengths & Key Advantages
- 1M bağlam penceresi ve yanıt başına maksimum 32K çıktı tokenı kapasitesi (SWE-bench Verified 73.5% · GPQA Diamond 78.5%)
- Sadece 580 ms ilk token gecikmesi (TTFT) ile saniyede 80 token yüksek üretim hızı
- İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $1.8/$7.2 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-6 Astra | Qwen3.7 Max |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.15 | $0.38 |
Output Tokens / Task Tokens generated per task | 58K | 32K |
Reasoning Tokens / Task Thinking tokens burned per task | 32K | 14K |
Teknik Özellikler
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-6 Astra | Qwen3.7 Max |
|---|---|---|
| Official API Model ID (SDK) | gpt-6-astra | qwen3-7-max-instruct |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Alibaba REST API (OpenAI-Compatible) |
| Release Date | 2026-09 | 2026-05 |
| Knowledge Cutoff | June 2026 | April 2026 |
| Architecture | Omni-Adaptive Autoregressive with Dynamic CoT | Next-Generation Deep Frontier Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($10/1M in) across full 272K window | Flat rate ($1.8/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $1/1M (no extra cache-write fee) | Cached input at $0.18/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) | Text BPE (~4 chars/token) |
| 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 | OpenAI Preparedness Framework Audited & System Card Published | Alibaba 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, vision, audio | text |
| Output Modalities | text, audio | text |
GPT-6 Astra vs Qwen3.7 Max: Hızlı Yanıtlar (SSS)
Which is more intelligent, GPT-6 Astra or Qwen3.7 Max?
GPT-6 Astra is more intelligent. It scores 96 compared with 92 on the composite Intelligence Index.
Which model is faster?
GPT-6 Astra is faster, generating 100 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
Qwen3.7 Max is cheaper at $1.21 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Qwen3.7 Max has lower latency, with a time to first token of 0.58s compared with 0.95s.
Which model has a larger context window?
Qwen3.7 Max has a larger context window, supporting 1M tokens compared with 272K tokens.
Sonuç
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., or choose Qwen3.7 Max for otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir..
Sıkça Sorulan Sorular (SSS)
Which is cheaper: GPT-6 Astra or Qwen3.7 Max?+
GPT-6 Astra costs $10/1M input and $50/1M output tokens, while Qwen3.7 Max costs $1.8/1M input and $7.2/1M output tokens.
Which model has a larger context window: GPT-6 Astra or Qwen3.7 Max?+
GPT-6 Astra supports 272K tokens whereas Qwen3.7 Max supports 1M 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.
Resmi kaynaklar: OpenAI & Alibaba Official Documentation