Head-to-Head Model Comparison

Qwen Plus vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
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Compare Qwen Plus by Alibaba against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Perbandingan Langsung (VS)

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Popular Matchups:
Alibaba

Qwen Plus

Model Generasi Klasik

Qwen Plus dari Alibaba adalah model AI yang dirancang untuk asisten percakapan, peringkasan dokumen, dan beban kerja bisnis umum, menghadirkan jendela konteks 1M, kecepatan 95 token/detik, indeks kecerdasan 75/100, serta tarif $0.4/$1.2 per

Intelligence Index75 / 100
Input Token:

$0.40 / 1M

Output Token:

$1.20 / 1M

Context Window:

1M tokens

SWE-bench Verified:

N/A

OpenAI

GPT-6.1 Sol

Model Unggulan Garis Depan

GPT-6.1 Sol dari OpenAI adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 1M, kecepatan 120 token/detik, indeks kecerdasan 94/100, serta tarif $2

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

Perbedaan Utama Sekilas

  • Qwen Plus is 7.0x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol is faster at 120 tok/s vs 95 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen PlusGPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
7594
Provider
AlibabaOpenAI
Input Price
Cost per million input tokens
$0.40 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$1.20 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.23 / 1M$1.47 / 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
8K128K
Throughput Speed
Tokens generated per second
95 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
N/A82.3%
GPQA Diamond
Graduate-level reasoning
42.5%80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.04 / 1M$0.10 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Qwen Plus
7.0x cheaper monthly runtime
Speed
GPT-6.1 Sol
+26% faster generation
Context
Tied
1M tokens window

Skor Benchmark Terverifikasi

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

Qwen PlusGPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

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

N/Avs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

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

42.5%vs80.8%
MMLU-Pro (Multi-task Language Understanding)

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

74.5%vs89.9%
LMSYS Chatbot Arena Elo

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

1260ptsvs1519pts
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.

N/Avs79.7%
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.

95 tok/s vs120 tok/s

Latensi & Waktu Respons

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
Qwen Plus0.42s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen Plus5.68s
GPT-6.1 Sol5.29s

Simulator Biaya Token Interaktif

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)
Qwen Plus Monthly API Bill
$1.74 / month
$0.4/1M in · $1.2/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Qwen Plus saves approximately $10.41 / month (86%) under this workload.7.0x Savings

Qwen Plus · Strengths & Key Advantages

  • Jendela konteks 1M dengan kapasitas output maksimum hingga 8K token (GPQA Diamond 42.5% · MMLU-Pro 74.5%)
  • Kecepatan generasi tinggi 95 token/detik dengan latensi token pertama (TTFT) hanya 420 ms
  • Skema harga API kompetitif (tarif $0.4/$1.2 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

GPT-6.1 Sol · Strengths & Key Advantages

  • Jendela konteks 1M dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 82.3% · GPQA Diamond 80.8%)
  • Kecepatan generasi tinggi 120 token/detik dengan latensi token pertama (TTFT) hanya 1120 ms
  • Skema harga API kompetitif (tarif $2/$10 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

Token Use & Task Economics

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

MetricQwen PlusGPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.08$2.05
Output Tokens / Task
Tokens generated per task
15K62K
Reasoning Tokens / Task
Thinking tokens burned per task
4K36K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureQwen PlusGPT-6.1 Sol
Official API Model ID (SDK)qwen-plus-instructgpt-6-1-sol
API ProtocolAlibaba REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2024-012026-09
Knowledge CutoffSeptember 2024April 2026
ArchitectureHigh-Throughput Dense Autoregressive 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 ($0.4/1M in) across full 1000K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.04/1M 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

Qwen Plus vs GPT-6.1 Sol: Jawaban Cepat (FAQ)

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

GPT-6.1 Sol is more intelligent. It scores 94 compared with 75 on the composite Intelligence Index.

Which model is faster?

GPT-6.1 Sol is faster, generating 120 tokens per second compared with 95 tokens per second.

Which model is cheaper to run?

Qwen Plus is cheaper at $0.23 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Qwen Plus has lower latency, with a time to first token of 0.42s compared with 1.12s.

Kesimpulan

Choose Qwen Plus for sangat cocok untuk asisten percakapan, peringkasan dokumen, dan beban kerja bisnis umum, sistem rag perusahaan, dan integrasi api skala produksi., or choose GPT-6.1 Sol for sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi ai, sistem rag perusahaan, dan integrasi api skala produksi..

Pertanyaan Umum (FAQ)

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

Qwen Plus costs $0.4/1M input and $1.2/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

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

Qwen Plus supports 1M 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.

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.

Sumber resmi: Alibaba & OpenAI Official Documentation