QwQ Plus vs Qwen Max
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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QwQ Plus by Alibaba and Qwen 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, QwQ Plus holds a notable pricing advantage for token ingestion. On output generation, QwQ Plus is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, QwQ Plus provides an expanded memory horizon with 131K tokens. In latency-sensitive production environments, QwQ 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.
원하는 AI 모델 선택 및 실시간 비교
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
QwQ Plus
심층 추론 모델Alibaba의 QwQ Plus 모델은 131K 토큰 컨텍스트 윈도우와 입력 $0.4/1M 토큰, 출력 $1.6/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$0.40 / 1M
$1.60 / 1M
131.1K tokens
45%
Qwen Max
심층 추론 모델Alibaba의 Qwen Max 모델은 32K 토큰 컨텍스트 윈도우와 입력 $1.6/1M 토큰, 출력 $6.4/1M 토큰의 합리적인 API 요금을 제공하며 코딩, 추론 및 엔터프라이즈 자동화에 최적화되어 있습니다.
$1.60 / 1M
$6.40 / 1M
32.8K tokens
32.5%
한눈에 보는 핵심 차이점
- QwQ Plus is 4.0x cheaper for API usage (input + output tokens combined).
- QwQ Plus has a larger context window (131K vs 33K tokens).
- QwQ Plus is faster at 70 tok/s vs 65 tok/s.
- QwQ Plus leads on SWE-bench coding (45.0% vs 32.5%).
| Feature | QwQ Plus | Qwen Max |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 84 | 78 |
Provider | Alibaba | Alibaba |
Input Price Cost per million input tokens | $0.40 / 1M | $1.60 / 1M |
Output Price Cost per million output tokens | $1.60 / 1M | $6.40 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.27 / 1M | $1.07 / 1M |
Context Window Maximum input + output tokens | 131.1K tokens~197 A4 pages of text | 32.8K tokens~49 A4 pages of text |
Max Output Tokens Per single request | 16K | 8K |
Throughput Speed Tokens generated per second | 70 tok/s | 65 tok/s |
SWE-bench Verified Real-world software engineering | 45% | 32.5% |
GPQA Diamond Graduate-level reasoning | 65.2% | 48% |
Cached Input Price Prompt caching discount per 1M tokens | $0.04 / 1M | $0.16 / 1M |
부문별 우위 모델
At-a-glance decision framework검증된 벤치마크 점수 비교
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.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Tokens emitted per second during active generation streaming.
지연 시간(Latency) 및 응답 속도
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
실시간 API 토큰 비용 시뮬레이터
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
QwQ Plus · Strengths & Key Advantages
- Alibaba의 첨단 Deep Reasoning Chain-of-Thought Transformer 아키텍처와 최대 131K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $0.4/1M, 출력 $1.6/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Qwen Max · Strengths & Key Advantages
- Alibaba의 첨단 Dense Autoregressive Transformer with Multi-Head Attention 아키텍처와 최대 32K 토큰 컨텍스트 지원
- 경쟁력 있는 API 가격(입력 $1.6/1M, 출력 $6.4/1M)과 빠른 응답 속도
- 코드 생성, 복잡한 논리 추론 및 다국어 벤치마크에서 검증된 성능 발휘
Considerations & Trade-offs
- 대규모 장문 컨텍스트 처리 시 토큰 비용 및 호출 한도 관리가 필요함
- 특수 도메인 작업에서는 정교한 프롬프트 엔지니어링과 RAG 연동이 권장됨
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | QwQ Plus | Qwen Max |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.12 | $0.18 |
Output Tokens / Task Tokens generated per task | 24K | 18K |
Reasoning Tokens / Task Thinking tokens burned per task | 14K | 6K |
기술 사양 (Specifications)
Architecture, release timeline, capabilities, and modalities.
| Feature | QwQ Plus | Qwen Max |
|---|---|---|
| Official API Model ID (SDK) | qwq-plus-instruct | qwen-max-instruct |
| API Protocol | Alibaba REST API (OpenAI-Compatible) | Alibaba REST API (OpenAI-Compatible) |
| Release Date | 2025-03 | 2024-04 |
| Knowledge Cutoff | January 2025 | September 2023 |
| Architecture | Deep Reasoning Chain-of-Thought Transformer | Dense Autoregressive Transformer with Multi-Head Attention |
| Parameters | 32B (Distilled Reasoning Engine) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.4/1M in) across full 131K window | Flat rate ($1.6/1M in) across full 33K window |
| Prompt Cache Policy & TTL | Cached input at $0.04/1M tokens | Cached input at $0.16/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | 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 | Alibaba Production Safety & Alignment Verified | 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 | text |
| Output Modalities | text | text |
QwQ Plus vs Qwen Max: 핵심 요약 문답 (FAQ)
Which is more intelligent, QwQ Plus or Qwen Max?
QwQ Plus is more intelligent. It scores 84 compared with 78 on the composite Intelligence Index.
Which model is faster?
QwQ Plus is faster, generating 70 tokens per second compared with 65 tokens per second.
Which model is cheaper to run?
QwQ Plus is cheaper at $0.27 per 1M tokens blended, compared with $1.07 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Qwen Max has lower latency, with a time to first token of 0.58s compared with 0.85s.
Which model has a larger context window?
QwQ Plus has a larger context window, supporting 131.1K tokens compared with 32.8K tokens.
종합 평가
Verdict & Model Selection Recommendation: Choose QwQ Plus if your priority is Mathematical proofs, algorithmic debugging, competitive programming, and formal verification. Its performance in demanding tasks justifies its operational token cost. Choose Qwen Max if your workflow prioritizes Multilingual enterprise chat, customer support, and general NLP automation. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
자주 묻는 질문 (FAQ)
How does QwQ Plus compare to Qwen Max in API token pricing and cost per token?+
QwQ Plus costs $0.40 per 1M input tokens and $1.60 per 1M output tokens, whereas Qwen Max costs $1.60 input and $6.40 output. Overall, QwQ 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: QwQ Plus or Qwen Max?+
QwQ Plus supports a context window of 131K tokens (~98k words), while Qwen Max supports 33K tokens (~25k words). Therefore, QwQ Plus can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: QwQ Plus or Qwen Max?+
QwQ Plus scores 45% on SWE-bench Verified while Qwen Max scores 32.5%. For autonomous software engineering and multi-file debugging, QwQ Plus holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between QwQ Plus and Qwen Max?+
QwQ Plus features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Qwen Max provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between QwQ Plus and Qwen Max?+
QwQ Plus generates approximately 70 tokens per second, while Qwen Max delivers 65 tokens per second. In latency-sensitive production environments, QwQ Plus provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining QwQ Plus and Qwen Max to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to QwQ Plus to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Qwen Max. This tiered routing pattern cuts overall API bills by up to 70%.
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.
공식 출처: GetInfoUs Independent AI Benchmarks & Official API Specs