Head-to-Head Model Comparison

Qwen3.5 Plus vs Qwen3 Max

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs अनुसंधान दल द्वारा समीक्षितअंतिम समीक्षा: October 2026संपादकीय नीति
साझा करें
Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Qwen3.5 Plus vs Qwen3 Max: Benchmarks, Pricing & Speed Comparison

Qwen3.5 Plus by Alibaba and Qwen3 Max by Alibaba represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Qwen3.5 Plus holds a notable pricing advantage for token ingestion. On output generation, Qwen3.5 Plus is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Qwen3.5 Plus provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, Qwen3.5 Plus leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

आमने-सामने मॉडल तुलना (VS)

किसी भी मॉडल को बदलें और तुलना करें

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench
Popular Matchups:
Alibaba

Qwen3.5 Plus

डीप रीजनिंग मॉडल

Alibaba द्वारा विकसित Qwen3.5 Plus एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $0.6/1M इनपुट तथा $2.4/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index87 / 100
Input Token:

$0.60 / 1M

Output Token:

$2.40 / 1M

Context Window:

1M tokens

SWE-bench Verified:

64%

Alibaba

Qwen3 Max

डीप रीजनिंग मॉडल

Alibaba द्वारा विकसित Qwen3-Max एक उन्नत AI मॉडल है, जिसमें 262K टोकन का कॉन्टेक्स्ट विंडो और $2.0/1M इनपुट तथा $6.0/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।

Intelligence Index88 / 100
Input Token:

$2.00 / 1M

Output Token:

$6.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

62.5%

एक नज़र में मुख्य अंतर

  • Qwen3.5 Plus is 2.9x cheaper for API usage (input + output tokens combined).
  • Qwen3.5 Plus has a larger context window (1M vs 262K tokens).
  • Qwen3.5 Plus is faster at 85 tok/s vs 72 tok/s.
  • Qwen3.5 Plus leads on SWE-bench coding (64.0% vs 62.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen3.5 PlusQwen3 Max
Intelligence Index
Composite reasoning & knowledge score (0-100)
8788
Provider
AlibabaAlibaba
Input Price
Cost per million input tokens
$0.60 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$2.40 / 1M$6.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.40 / 1M$1.28 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text262.1K tokens~393 A4 pages of text
Max Output Tokens
Per single request
16K16K
Throughput Speed
Tokens generated per second
85 tok/s72 tok/s
SWE-bench Verified
Real-world software engineering
64%62.5%
GPQA Diamond
Graduate-level reasoning
72%71.2%
Cached Input Price
Prompt caching discount per 1M tokens
$0.06 / 1M$0.40 / 1M

किस क्षेत्र में कौन आगे है?

At-a-glance decision framework
Coding
Qwen3.5 Plus
+1.5% SWE-bench lead
Cost
Qwen3.5 Plus
2.9x cheaper monthly runtime
Speed
Qwen3.5 Plus
+18% faster generation
Context
Qwen3.5 Plus
1M tokens window

सत्यापित बेंचमार्क स्कोर तुलना

Official evaluation metrics verified by independent third-party research labs.

Qwen3.5 PlusQwen3 Max
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

64%vs62.5%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

72%vs71.2%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

85%vs84.5%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1410ptsvs1395pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs72 tok/s

लेटेंसी और रिस्पॉन्स समय

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Qwen3.5 Plus0.49s
Qwen3 Max0.59s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen3.5 Plus6.37s
Qwen3 Max7.53s

रियल-टाइम टोकन लागत सिम्युलेटर

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Qwen3.5 Plus Monthly API Bill
$3.15 / month
$0.6/1M in · $2.4/1M out
Qwen3 Max Monthly API Bill
$9.00 / month
$2/1M in · $6/1M out
Qwen3.5 Plus saves approximately $5.85 / month (65%) under this workload.2.9x Savings

Qwen3.5 Plus · Strengths & Key Advantages

  • Alibaba की उन्नत Enterprise Million-Token Multimodal Transformer आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($0.6/1M इनपुट, $2.4/1M 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

Qwen3 Max · Strengths & Key Advantages

  • Alibaba की उन्नत Advanced Dense/MoE Hybrid Frontier Transformer आर्किटेक्चर और 262K कॉन्टेक्स्ट विंडो क्षमता
  • किफायती और पारदर्शी API मूल्य ($2.0/1M इनपुट, $6.0/1M 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.

MetricQwen3.5 PlusQwen3 Max
Cost per Task
Estimated USD to finish one task
$0.19$0.28
Output Tokens / Task
Tokens generated per task
24K25K
Reasoning Tokens / Task
Thinking tokens burned per task
8K10K

तकनीकी विशिष्टताएँ (Specs)

Architecture, release timeline, capabilities, and modalities.

FeatureQwen3.5 PlusQwen3 Max
Official API Model ID (SDK)qwen3-5-plus-instructqwen3-max-instruct
API ProtocolAlibaba REST API (OpenAI-Compatible)Alibaba REST API (OpenAI-Compatible)
Release Date2026-022025-09
Knowledge CutoffDecember 2025July 2025
ArchitectureEnterprise Million-Token Multimodal TransformerAdvanced Dense/MoE Hybrid Frontier Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.6/1M in) across full 1000K windowFlat rate ($2/1M in) across full 262K window
Prompt Cache Policy & TTLCached input at $0.06/1M tokensCached input at $0.4/1M tokens
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMCloud-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 ClassificationAlibaba Production Safety & Alignment VerifiedAlibaba Production Safety & Alignment Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext
Output Modalitiestexttext

Qwen3.5 Plus vs Qwen3 Max: त्वरित प्रश्नोत्तर (FAQ)

Which is more intelligent, Qwen3.5 Plus or Qwen3 Max?

Qwen3 Max is more intelligent. It scores 88 compared with 87 on the composite Intelligence Index.

Which model is faster?

Qwen3.5 Plus is faster, generating 85 tokens per second compared with 72 tokens per second.

Which model is cheaper to run?

Qwen3.5 Plus is cheaper at $0.40 per 1M tokens blended, compared with $1.28 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3.5 Plus has lower latency, with a time to first token of 0.49s compared with 0.59s.

Which model has a larger context window?

Qwen3.5 Plus has a larger context window, supporting 1M tokens compared with 262.1K tokens.

निष्कर्ष

Verdict & Model Selection Recommendation: Choose Qwen3.5 Plus if your priority is Multimodal enterprise document analysis, long-context codebases, and autonomous web agents. Its performance in demanding tasks justifies its operational token cost. Choose Qwen3 Max if your workflow prioritizes Complex multi-turn agents, enterprise strategic planning, and automated STEM research. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

अक्सर पूछे जाने वाले प्रश्न (FAQ)

How does Qwen3.5 Plus compare to Qwen3 Max in API token pricing and cost per token?+

Qwen3.5 Plus costs $0.60 per 1M input tokens and $2.40 per 1M output tokens, whereas Qwen3 Max costs $2.00 input and $6.00 output. Overall, Qwen3.5 Plus is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Qwen3.5 Plus or Qwen3 Max?+

Qwen3.5 Plus supports a context window of 1,000K tokens (~750k words), while Qwen3 Max supports 262K tokens (~197k words). Therefore, Qwen3.5 Plus can process more textual data and document context in a single prompt.

Which AI model is better for software engineering and coding: Qwen3.5 Plus or Qwen3 Max?+

Qwen3.5 Plus scores 64% on SWE-bench Verified while Qwen3 Max scores 62.5%. For autonomous software engineering and multi-file debugging, Qwen3.5 Plus holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Qwen3.5 Plus and Qwen3 Max?+

Qwen3.5 Plus features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Qwen3 Max provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Qwen3.5 Plus and Qwen3 Max?+

Qwen3.5 Plus generates approximately 85 tokens per second, while Qwen3 Max delivers 72 tokens per second. In latency-sensitive production environments, Qwen3.5 Plus provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Qwen3.5 Plus and Qwen3 Max to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Qwen3.5 Plus to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Qwen3 Max. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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: GetInfoUs Independent AI Benchmarks & Official API Specs