Qwen / Alibaba•Rank #52

Qwen3.7-Plus

Proprietarygeneralreasoning

Leaderboard Score

43.3

Scale: 0 - 100

Throughput Speed

50 tps

Context Window

API Pricing / 1M

$0.50

Parameter Scale

Proprietary

Verified AI Radar & Benchmarks•8 Evaluated Metrics

Capability Radar & Benchmark Scores

Multi-Axis Capability Radar

Comparing Qwen3.7-Plus against Frontier Top 10 & Open-Source average

0 - 100 Scale

Qwen3.7-Plus

Frontier Top 10 Avg

Open-Source Avg

Performance Vectors

Where Qwen3.7-Plus Leads

Coding & SWETop 10: 79.1% • OS: 47.6%

32.5%-46.6% vs Top 10

Reasoning & MathTop 10: 74.6% • OS: 46.6%

43.6%-31.0% vs Top 10

Agent & Tool AutomationTop 10: 71.2% • OS: 31.9%

26.1%-45.1% vs Top 10

Terminal & CLI ExecutionTop 10: 80.4% • OS: 47.6%

32.5%-47.9% vs Top 10

MMLU & Knowledge QATop 10: 50% • OS: 86.7%

54.1%+4.1% vs Top 10

Cyber & Security ExploitsTop 10: 87.8% • OS: 80.6%

41.1%-46.7% vs Top 10

All Verified Benchmark Evaluations

Direct Pass@1 and resolution rates across standardized evaluations.

OverallCodingReasoningAgenticTerminal

Featured Compute Platform

Run Benchmarks on Dedicated AI Clusters

Zero-cold-start inference endpoints with dedicated GPU instances.

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Executive Analysis & Verdict

Qwen3.7-Plus by Alibaba Cloud / Qwen Team is a proprietary Large Language Model ranking #36 globally with an overall benchmark score of 43.3.

Key Strengths & Highlights

•High overall benchmark score of 43.3 on frontier evaluation suites
•Robust reasoning performance (43.6) and coding accuracy (32.5)
•Optimized inference throughput with extended token context

Limitations & Considerations

•Subject to standard provider rate limits and API quota

Recommended Workflows

Enterprise production applications, coding assistance, and advanced reasoning

Architectural Overview & Capability Profile

Qwen3.7-Plus is developed by Qwen as an advanced foundation model engineered for production enterprise applications, reasoning workflows, and autonomous problem-solving. On the comprehensive RankLLMs composite evaluation index, Qwen3.7-Plus registers an overall benchmark rating of 43.3 / 100.

Operating under a Proprietary license structure, Qwen3.7-Plus is served via high-throughput managed API endpoints designed for low-latency production queries.

Benchmark Performance & Real-World Utility

In standardized laboratory and real-world evaluation suites, Qwen3.7-Plus demonstrates calibrated proficiency across key performance vectors:

SWE-bench Verified Software Engineering (32.5%): Measures multi-file GitHub issue resolution. The model demonstrates practical capability in localizing source code bugs, synthesizing functional patches, and passing rigorous integration test matrices. For evaluation methodology, consult our SWE-bench Pro guide.
GPQA Diamond Scientific Reasoning (43.6%): Assesses graduate-level domain problem solving across physics, chemistry, and biology, minimizing hallucinations in multi-step deductive arguments. See our Humanity’s Last Exam benchmark analysis.
MATH-500 Competition Mathematics (43.6%): Evaluates formal mathematical problem solving and symbolic derivation, providing foundational logic for algorithmic computing.
Terminal-Bench Execution (32.5%): Reflects proficiency in interactive command-line environments, shell tool use, and automated DevOps scripting.
Code Arena Preference Rating (1235 Elo): Validates human developer satisfaction in blind side-by-side coding evaluations against contemporary alternatives.

Inference Latency & Cost Architecture

Token Context Window: 1.0M tokens, allowing large documents, multi-file codebases, and long conversation memories to be processed in a single context window.
Inference Speed: Reference throughput clocks at approximately 50 tokens/second, enabling responsive streaming in developer tools and interactive interfaces.
Commercial Pricing: API consumption is billed at $0.50 per 1M input tokens and $3.00 per 1M output tokens, offering predictable scaling for high-volume enterprise traffic.

Strengths, Limitations & Ideal Workflows

Primary Strengths

High overall benchmark score of 43.3 on frontier evaluation suites
Robust reasoning performance (43.6) and coding accuracy (32.5)
Optimized inference throughput with extended token context

Known Considerations

Subject to standard provider rate limits and API quota

Recommended Use Cases

Enterprise production applications, coding assistance, and advanced reasoning.

Compare with alternatives in the Model Comparison Engine
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Explore top coding models in our Best LLM for Coding Guide

Frequently Asked Questions About Qwen3.7-Plus

What is Qwen3.7-Plus and who developed it?↓

Qwen3.7-Plus is a proprietary large language model developed by Qwen / Alibaba. It ranks #52 on the RankLLMs composite leaderboard, ahead of 40% of the 85 models we track, with an overall score of 43.3 / 100.

Can Qwen3.7-Plus handle very long documents and codebases?↓

Qwen3.7-Plus supports a 1.0M-token input context window and generates about 50 tps tokens per second in our reference measurements and which is enough to hold entire repositories, long transcripts, or multi-document research sets in a single session..

How much does Qwen3.7-Plus cost per million tokens?↓

API pricing for Qwen3.7-Plus is $0.50 per 1M tokens - cheaper than 61% of priced models we track. Confirm the current rate on the provider's official pricing page before budgeting.

What is Qwen3.7-Plus best at?↓

Qwen3.7-Plus is strongest in High overall benchmark score of 43.3 on frontier evaluation suites; Robust reasoning performance (43.6) and coding accuracy (32.5); Optimized inference throughput with extended token context. Full pillar-by-pillar numbers are in the benchmark tables above.

What should you watch out for with Qwen3.7-Plus?↓

Known trade-offs include: Subject to standard provider rate limits and API quota. Weigh these against the strengths above for your specific workload.