Head-to-Head Model Comparison

Qwen3.7 Max vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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AlibabaAnthropicflagshipflagship

Compare Qwen3.7 Max by Alibaba against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Head-to-Head Comparison

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Popular Matchups:
Alibaba

Qwen3.7 Max

Agent Flagship

Alibaba's mid-2026 definitive frontier foundation model delivering autonomous agent execution, 1M token context, and world-class STEM reasoning.

Intelligence Index92 / 100
Input Token:

$1.80 / 1M

Output Token:

$7.20 / 1M

Context Window:

1M tokens

SWE-bench Verified:

73.5%

Anthropic

Claude Opus 5.5

Frontier Intelligence Titan

Anthropic's most intelligent model for complex reasoning, research, and strategic analysis.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Key Differences at a Glance

  • 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%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen3.7 MaxClaude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
9294
Provider
AlibabaAnthropic
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 text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
32K128K
Throughput Speed
Tokens generated per second
80 tok/s78 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

Who Wins Where?

At-a-glance decision framework
Coding
Claude Opus 5.5
+11.1% SWE-bench lead
Cost
Qwen3.7 Max
2.6x cheaper monthly runtime
Speed
Qwen3.7 Max
+3% faster generation
Context
Tied
1M tokens window

Empirical Head-to-Head Benchmark Scores

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

Qwen3.7 MaxClaude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

73.5%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

78.5%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs91.5%
LMSYS Chatbot Arena Elo

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

1470ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs66.4%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs83.1%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

86%vs95.4%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

80 tok/s vs78 tok/s

Latency & Response Time

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
Qwen3.7 Max0.58s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen3.7 Max6.83s
Claude Opus 5.57.81s

Real-Time Interactive Token Cost Simulator

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)
Qwen3.7 Max Monthly API Bill
$9.45 / month
$1.8/1M in · $7.2/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Qwen3.7 Max saves approximately $15.15 / month (62%) under this workload.2.6x Savings

Qwen3.7 Max · Strengths & Key Advantages

  • Chatbot Arena Elo of 1470 placing it in the top 3 global foundation models
  • Million-token context window with deep needle-in-a-haystack recall fidelity
  • 73.5% SWE-bench Verified score enabling true production software engineering
Considerations & Trade-offs
  • Text-focused architecture requires pairing with vision endpoints for visual input
  • Premium pricing compared to the economical Qwen Plus/Flash tiers

Claude Opus 5.5 · Strengths & Key Advantages

  • Unmatched autonomous multi-step agentic coding and refactoring
  • Flawless multi-document reasoning over 1M token context with no long-prompt surcharge
  • Highest composite Intelligence Index score measured (94/100), leading SWE-bench Verified at 84.6%
  • Precise tool execution with robust error-recovery loops
Considerations & Trade-offs
  • Premium output pricing ($20.00/M) plus heavy reasoning-token usage (~68K output tokens per complex task) keeps long agentic runs expensive
  • Long thinking times at maximum effort can push a single hard agentic task toward ~$3.85+

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricQwen3.7 MaxClaude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.38$3.85
Output Tokens / Task
Tokens generated per task
32K68K
Reasoning Tokens / Task
Thinking tokens burned per task
14K42K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeatureQwen3.7 MaxClaude Opus 5.5
Official API Model ID (SDK)qwen3-7-max-instructclaude-opus-5-5-20260901
API ProtocolAlibaba REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-052026-09
Knowledge CutoffApril 2026June 2026
ArchitectureNext-Generation Deep Frontier Reasoning TransformerExtended Autonomous Hybrid Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM4,000 – 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 windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.18/1M tokens$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
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 toolsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
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 VerifiedAnthropic 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 TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision
Output Modalitiestexttext

Qwen3.7 Max vs Claude Opus 5.5: Quick Answers

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.

Verdict

Choose Qwen3.7 Max for autonomous engineering agents, enterprise legal/financial due diligence, and scientific research, or choose Claude Opus 5.5 for large-scale software development agents, enterprise codebases, and mission-critical scientific synthesis.

Frequently asked questions

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.

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.

Sources: Alibaba & Anthropic Official Documentation