Qwen3.7 Max vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Qwen3.7 Max by Alibaba against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.
किसी भी मॉडल को बदलें और तुलना करें
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Live comparison: no in-depth editorial review has been published for this pair yet.
Qwen3.7 Max
डीप रीजनिंग मॉडलAlibaba द्वारा विकसित Qwen3.7 Max एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $1.8/1M इनपुट तथा $7.2/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$1.80 / 1M
$7.20 / 1M
1M tokens
73.5%
Claude Opus 5.5
डीप रीजनिंग मॉडलAnthropic द्वारा विकसित Claude Opus 5.5 एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $4.0/1M इनपुट तथा $20.0/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
एक नज़र में मुख्य अंतर
- Qwen3.7 Max is 2.6x cheaper for API usage (input + output tokens combined).
- Qwen3.7 Max is faster at 80 tok/s vs 78 tok/s.
- Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 73.5%).
| Feature | Qwen3.7 Max | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 92 | 94 |
Provider | Alibaba | Anthropic |
Input Price Cost per million input tokens | $1.80 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $7.20 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.21 / 1M | $3.08 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 32K | 128K |
Throughput Speed Tokens generated per second | 80 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | 73.5% | 84.6% |
GPQA Diamond Graduate-level reasoning | 78.5% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.18 / 1M | $0.40 / 1M |
किस क्षेत्र में कौन आगे है?
At-a-glance decision frameworkसत्यापित बेंचमार्क स्कोर तुलना
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.
लेटेंसी और रिस्पॉन्स समय
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
रियल-टाइम टोकन लागत सिम्युलेटर
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Qwen3.7 Max · Strengths & Key Advantages
- Alibaba की उन्नत Next-Generation Deep Frontier Reasoning Transformer आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($1.8/1M इनपुट, $7.2/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
Claude Opus 5.5 · Strengths & Key Advantages
- Anthropic की उन्नत Extended Autonomous Hybrid Reasoning Transformer आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($4.0/1M इनपुट, $20.0/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Qwen3.7 Max | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.38 | $3.85 |
Output Tokens / Task Tokens generated per task | 32K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 14K | 42K |
तकनीकी विशिष्टताएँ (Specs)
Architecture, release timeline, capabilities, and modalities.
| Feature | Qwen3.7 Max | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | qwen3-7-max-instruct | claude-opus-5-5-20260901 |
| API Protocol | Alibaba REST API (OpenAI-Compatible) | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-05 | 2026-09 |
| Knowledge Cutoff | April 2026 | June 2026 |
| Architecture | Next-Generation Deep Frontier Reasoning Transformer | Extended Autonomous Hybrid Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($1.8/1M in) across full 1000K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.18/1M tokens | $0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| 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 Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| 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 |
| Output Modalities | text | text |
Qwen3.7 Max vs Claude Opus 5.5: त्वरित प्रश्नोत्तर (FAQ)
Which is more intelligent, Qwen3.7 Max or Claude Opus 5.5?
Claude Opus 5.5 is more intelligent. It scores 94 compared with 92 on the composite Intelligence Index.
Which model is faster?
Qwen3.7 Max is faster, generating 80 tokens per second compared with 78 tokens per second.
Which model is cheaper to run?
Qwen3.7 Max is cheaper at $1.21 per 1M tokens blended, compared with $3.08 (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 1.40s.
निष्कर्ष
Choose Qwen3.7 Max for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और alibaba आधारित प्रोडक्शन सिस्टम, or choose Claude Opus 5.5 for एंटरप्राइज ऑटोमेशन, सॉफ्टवेयर डेवलपमेंट, ai एजेंट्स और anthropic आधारित प्रोडक्शन सिस्टम.
अक्सर पूछे जाने वाले प्रश्न (FAQ)
Which is cheaper: Qwen3.7 Max or Claude Opus 5.5?+
Qwen3.7 Max costs $1.8/1M input and $7.2/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.
Which model has a larger context window: Qwen3.7 Max or Claude Opus 5.5?+
Qwen3.7 Max supports 1M tokens whereas Claude Opus 5.5 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.
स्रोत: Alibaba & Anthropic Official Documentation