Qwen3 Max vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Qwen3 Max by Alibaba against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Qwen3 Max
Derin Akıl Yürütme ModeliAlibaba tarafından geliştirilen Qwen3-Max, 262K token bağlam penceresi ve 1M girdi başına $2.0, 1M çıktı başına $6.0 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.
$2.00 / 1M
$6.00 / 1M
262.1K tokens
62.5%
GPT-6 Astra
Derin Akıl Yürütme ModeliOpenAI tarafından geliştirilen GPT-6 Astra, 1M token bağlam penceresi ve 1M girdi başına $10.0, 1M çıktı başına $50.0 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Bir Bakışta Temel Farklar
- Qwen3 Max is 6.8x cheaper for API usage (input + output tokens combined).
- GPT-6 Astra has a larger context window (272K vs 262K tokens).
- GPT-6 Astra is faster at 100 tok/s vs 72 tok/s.
- GPT-6 Astra leads on SWE-bench coding (82.4% vs 62.5%).
| Feature | Qwen3 Max | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 88 | 96 |
Provider | Alibaba | OpenAI |
Input Price Cost per million input tokens | $2.00 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $6.00 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.28 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 262.1K tokens~393 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 16K | 128K |
Throughput Speed Tokens generated per second | 72 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | 62.5% | 82.4% |
GPQA Diamond Graduate-level reasoning | 71.2% | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.40 / 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.
Qwen3 Max · Strengths & Key Advantages
- Alibaba imzalı gelişmiş Advanced Dense/MoE Hybrid Frontier Transformer mimarisi ve 262K token bağlam kapasitesi
- Dengeli API maliyeti ($2.0/1M girdi, $6.0/1M çıktı) ve yüksek yanıt hızı
- Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
- Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
- Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir
GPT-6 Astra · Strengths & Key Advantages
- OpenAI imzalı gelişmiş Omni-Adaptive Autoregressive with Dynamic CoT mimarisi ve 1M token bağlam kapasitesi
- Dengeli API maliyeti ($10.0/1M girdi, $50.0/1M çıktı) ve yüksek yanıt hızı
- Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
- Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
- Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Qwen3 Max | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.28 | $2.15 |
Output Tokens / Task Tokens generated per task | 25K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 10K | 32K |
Teknik Özellikler
Architecture, release timeline, capabilities, and modalities.
| Feature | Qwen3 Max | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | qwen3-max-instruct | gpt-6-astra |
| API Protocol | Alibaba REST API (OpenAI-Compatible) | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-09 | 2026-09 |
| Knowledge Cutoff | July 2025 | June 2026 |
| Architecture | Advanced Dense/MoE Hybrid Frontier Transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | Confidential | 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 ($2/1M in) across full 262K window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.4/1M 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 | Alibaba 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 |
Qwen3 Max vs GPT-6 Astra: Hızlı Yanıtlar (SSS)
Which is more intelligent, Qwen3 Max or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 compared with 88 on the composite Intelligence Index.
Which model is faster?
GPT-6 Astra is faster, generating 100 tokens per second compared with 72 tokens per second.
Which model is cheaper to run?
Qwen3 Max is cheaper at $1.28 per 1M tokens blended, compared with $7.70 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Qwen3 Max has lower latency, with a time to first token of 0.59s compared with 0.95s.
Which model has a larger context window?
GPT-6 Astra has a larger context window, supporting 272K tokens compared with 262.1K tokens.
Sonuç
Choose Qwen3 Max for kurumsal otomasyon, yazılım mühendisliği, otonom yz ajanları ve alibaba tabanlı üretim sistemleri, or choose GPT-6 Astra for kurumsal otomasyon, yazılım mühendisliği, otonom yz ajanları ve openai tabanlı üretim sistemleri.
Sıkça Sorulan Sorular (SSS)
Which is cheaper: Qwen3 Max or GPT-6 Astra?+
Qwen3 Max costs $2/1M input and $6/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Qwen3 Max or GPT-6 Astra?+
Qwen3 Max supports 262K 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.
Resmi kaynaklar: Alibaba & OpenAI Official Documentation