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Head-to-Head Model Comparison

Qwen3 Coder Plus vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs 연구팀 검토 완료최종 검토일: October 2026편집 정책
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Compare Qwen3 Coder Plus by Alibaba against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

1:1 모델 맞대결 비교 (VS)

원하는 AI 모델 선택 및 실시간 비교

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

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Live comparison: no in-depth editorial review has been published for this pair yet.

Popular Matchups:
Alibaba

Qwen3 Coder Plus

플래그십 프론티어 모델

Alibaba의 Qwen3 Coder Plus 모델은 최첨단 엔터프라이즈 추론, 소프트웨어 개발 및 핵심 프로덕션 워크로드에 최적화된 AI 모델로, 1.0M 컨텍스트 윈도우, 초당 80 토큰의 생성 속도, 종합 지능 지수 85/100점(1M 토큰당 입력 $0.8 / 출력 $3.2)을 제공합니다.

Intelligence Index85 / 100
Input Token:

$0.80 / 1M

Output Token:

$3.20 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

54%

OpenAI

GPT-6.1 Sol

플래그십 프론티어 모델

OpenAI의 GPT-6.1 Sol 모델은 최첨단 엔터프라이즈 추론, 소프트웨어 개발 및 핵심 프로덕션 워크로드에 최적화된 AI 모델로, 1M 컨텍스트 윈도우, 초당 120 토큰의 생성 속도, 종합 지능 지수 94/100점(1M 토큰당 입력 $2 / 출력 $10)을 제공합니다.

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

한눈에 보는 핵심 차이점

  • Qwen3 Coder Plus is 2.9x cheaper for API usage (input + output tokens combined).
  • Qwen3 Coder Plus has a larger context window (1M vs 1M tokens).
  • GPT-6.1 Sol is faster at 120 tok/s vs 80 tok/s.
  • GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 54.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen3 Coder PlusGPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
8594
Provider
AlibabaOpenAI
Input Price
Cost per million input tokens
$0.80 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$3.20 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.54 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,573 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
16K128K
Throughput Speed
Tokens generated per second
80 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
54%82.3%
GPQA Diamond
Graduate-level reasoning
66.5%80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.08 / 1M$0.10 / 1M

부문별 우위 모델

At-a-glance decision framework
Coding
GPT-6.1 Sol
+28.3% SWE-bench lead
Cost
Qwen3 Coder Plus
2.9x cheaper monthly runtime
Speed
GPT-6.1 Sol
+50% faster generation
Context
Qwen3 Coder Plus
1.05M tokens window

검증된 벤치마크 점수 비교

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

Qwen3 Coder PlusGPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

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

54%vs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

66.5%vs80.8%
MMLU-Pro (Multi-task Language Understanding)

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

81%vs89.9%
LMSYS Chatbot Arena Elo

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

1340ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs63.6%
SciCode (Scientific Computing)

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

N/Avs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

71%vs79.7%
AIME (Advanced Math Competition)

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

N/Avs93.5%
Long-Context Reasoning

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

N/Avs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

80 tok/s vs120 tok/s

지연 시간(Latency) 및 응답 속도

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 Coder Plus0.51s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen3 Coder Plus6.76s
GPT-6.1 Sol5.29s

실시간 API 토큰 비용 시뮬레이터

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 Coder Plus Monthly API Bill
$4.20 / month
$0.8/1M in · $3.2/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Qwen3 Coder Plus saves approximately $7.95 / month (65%) under this workload.2.9x Savings

Qwen3 Coder Plus · Strengths & Key Advantages

  • 1.0M 컨텍스트 윈도우 및 최대 16K 출력 토큰 생성 지원 (SWE-bench Verified 54% · GPQA Diamond 66.5%)
  • 초당 80 토큰의 빠른 처리 속도와 510ms에 불과한 첫 토큰 지연 시간(TTFT)
  • 합리적인 API 요금 체계(1M 토큰당 입력 $0.8 / 출력 $3.2)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원
Considerations & Trade-offs
  • 독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
  • 초고난도 학술 연구 및 수학 증명 과제에서는 상위 대형 추론 특화 모델이 더 깊은 분석을 제공할 수 있습니다

GPT-6.1 Sol · Strengths & Key Advantages

  • 1M 컨텍스트 윈도우 및 최대 128K 출력 토큰 생성 지원 (SWE-bench Verified 82.3% · GPQA Diamond 80.8%)
  • 초당 120 토큰의 빠른 처리 속도와 1120ms에 불과한 첫 토큰 지연 시간(TTFT)
  • 합리적인 API 요금 체계(1M 토큰당 입력 $2 / 출력 $10)와 프롬프트 캐싱, 함수 호출 및 정형화된 JSON 출력 완벽 지원
Considerations & Trade-offs
  • 독점 클라우드 전용 모델로 로컬 오프라인 서버에 가중치를 다운로드하여 실행할 수 없습니다
  • 대규모 프로덕션 호출 환경에서는 비용 절감을 위해 프롬프트 캐싱과 배치 API(Batch API) 활용이 권장됩니다

Token Use & Task Economics

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

MetricQwen3 Coder PlusGPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.22$2.05
Output Tokens / Task
Tokens generated per task
22K62K
Reasoning Tokens / Task
Thinking tokens burned per task
7K36K

기술 사양 (Specifications)

Architecture, release timeline, capabilities, and modalities.

FeatureQwen3 Coder PlusGPT-6.1 Sol
Official API Model ID (SDK)qwen3-coder-plus-instructgpt-6-1-sol
API ProtocolAlibaba REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2025-072026-09
Knowledge CutoffMay 2025April 2026
ArchitectureHosted Enterprise Code-Specialized TransformerNear-Astra unified reasoning model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.8/1M in) across full 1049K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.08/1M tokensAutomatic prefix caching at $0.1/1M (no extra cache-write fee)
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 tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
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 VerifiedOpenAI Preparedness Framework Audited & System Card Published
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 Coder Plus vs GPT-6.1 Sol: 핵심 요약 문답 (FAQ)

Which is more intelligent, Qwen3 Coder Plus or GPT-6.1 Sol?

GPT-6.1 Sol is more intelligent. It scores 94 compared with 85 on the composite Intelligence Index.

Which model is faster?

GPT-6.1 Sol is faster, generating 120 tokens per second compared with 80 tokens per second.

Which model is cheaper to run?

Qwen3 Coder Plus is cheaper at $0.54 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen3 Coder Plus has lower latency, with a time to first token of 0.51s compared with 1.12s.

Which model has a larger context window?

Qwen3 Coder Plus has a larger context window, supporting 1.05M tokens compared with 1M tokens.

종합 평가

Choose Qwen3 Coder Plus for 최첨단 엔터프라이즈 추론, 소프트웨어 개발 및 핵심 프로덕션 워크로드, 엔터프라이즈 rag 지식베이스 및 대규모 프로덕션 api 연동에 최적., or choose GPT-6.1 Sol for 최첨단 엔터프라이즈 추론, 소프트웨어 개발 및 핵심 프로덕션 워크로드, 엔터프라이즈 rag 지식베이스 및 대규모 프로덕션 api 연동에 최적..

자주 묻는 질문 (FAQ)

Which is cheaper: Qwen3 Coder Plus or GPT-6.1 Sol?+

Qwen3 Coder Plus costs $0.8/1M input and $3.2/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Qwen3 Coder Plus or GPT-6.1 Sol?+

Qwen3 Coder Plus supports 1.0M tokens whereas GPT-6.1 Sol 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.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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: Alibaba & OpenAI Official Documentation