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Head-to-Head Model Comparison

Qwen-Omni Turbo vs GPT-Realtime-2.1

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Qwen-Omni Turbo vs GPT-Realtime-2.1: Benchmarks, Pricing & Speed Comparison

Qwen-Omni Turbo dari Alibaba dan GPT-Realtime-2.1 dari OpenAI adalah dua model AI unggulan. Qwen-Omni Turbo menawarkan jendela konteks 32.8K token dengan harga $0.30/$1.20 per 1 juta token, sedangkan GPT-Realtime-2.1 menyediakan konteks 128K token seharga $32.00/$64.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.

Perbandingan Langsung (VS)

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Alibaba

Qwen-Omni Turbo

Model Suara & Audio Asli

Qwen-Omni Turbo dari Alibaba adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 33K, kecepatan 90 token/detik, indeks kecerdasan 74/100, serta tarif $0

Intelligence Index74 / 100
Input Token:

$0.30 / 1M

Output Token:

$1.20 / 1M

Context Window:

32.8K tokens

SWE-bench Verified:

N/A

OpenAI

GPT-Realtime-2.1

Model Suara & Audio Asli

GPT-Realtime-2.1 dari OpenAI adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 128K, kecepatan 90 token/detik, indeks kecerdasan 65/100, serta tarif $

Intelligence Index65 / 100
Input Token:

$32.00 / 1M

Output Token:

$64.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

62%

Perbedaan Utama Sekilas

  • Qwen-Omni Turbo is 70.1x cheaper for API usage (input + output tokens combined).
  • GPT-Realtime-2.1 has a larger context window (128K vs 33K tokens).
  • GPT-Realtime-2.1 is faster at 90 tok/s vs 90 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureQwen-Omni TurboGPT-Realtime-2.1
Intelligence Index
Composite reasoning & knowledge score (0-100)
7465
Provider
AlibabaOpenAI
Input Price
Cost per million input tokens
$0.30 / 1M$32.00 / 1M
Output Price
Cost per million output tokens
$1.20 / 1M$64.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.20 / 1M$15.04 / 1M
Context Window
Maximum input + output tokens
32.8K tokens~49 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
8K33K
Throughput Speed
Tokens generated per second
90 tok/s90 tok/s
SWE-bench Verified
Real-world software engineering
N/A62%
GPQA Diamond
Graduate-level reasoning
N/A70%
Cached Input Price
Prompt caching discount per 1M tokens
$0.03 / 1M$3.20 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Qwen-Omni Turbo
70.1x cheaper monthly runtime
Speed
GPT-Realtime-2.1
+0% faster generation
Context
GPT-Realtime-2.1
128K tokens window

Skor Benchmark Terverifikasi

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

Qwen-Omni TurboGPT-Realtime-2.1
SWE-bench Verified (Autonomous Coding)

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

N/Avs62%
GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs70%
MMLU-Pro (Multi-task Language Understanding)

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

69%vs83%
LMSYS Chatbot Arena Elo

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

1235ptsvs1350pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs10.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs38%
SciCode (Scientific Computing)

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

N/Avs36.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs62%
AIME (Advanced Math Competition)

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

N/Avs86.5%
Long-Context Reasoning

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

N/Avs74%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs90 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-Omni Turbo0.38s
GPT-Realtime-2.10.32s
Est. End-to-End Response (500 tokens)TTFT + generation time
Qwen-Omni Turbo5.94s
GPT-Realtime-2.15.88s

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-Omni Turbo Monthly API Bill
$1.57 / month
$0.3/1M in · $1.2/1M out
GPT-Realtime-2.1 Monthly API Bill
$110.40 / month
$32/1M in · $64/1M out
Qwen-Omni Turbo saves approximately $108.83 / month (99%) under this workload.70.1x Savings

Qwen-Omni Turbo · Strengths & Key Advantages

  • Jendela konteks 33K dengan kapasitas output maksimum hingga 8K token (MMLU-Pro 69% · Arena Elo 1235)
  • Kecepatan generasi tinggi 90 token/detik dengan latensi token pertama (TTFT) hanya 380 ms
  • Skema harga API kompetitif (tarif $0.3/$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-Realtime-2.1 · Strengths & Key Advantages

  • Jendela konteks 128K dengan kapasitas output maksimum hingga 33K token (SWE-bench Verified 62% · GPQA Diamond 70%)
  • Kecepatan generasi tinggi 90 token/detik dengan latensi token pertama (TTFT) hanya 320 ms
  • Skema harga API kompetitif (tarif $32/$64 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-Omni TurboGPT-Realtime-2.1
Cost per Task
Estimated USD to finish one task
$0.06$6.66
Output Tokens / Task
Tokens generated per task
12K26K
Reasoning Tokens / Task
Thinking tokens burned per task
2K14K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureQwen-Omni TurboGPT-Realtime-2.1
Official API Model ID (SDK)qwen-omni-turbo-instructgpt-realtime-2-1
API ProtocolAlibaba REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2025-012026-07
Knowledge CutoffNovember 2024February 2026
ArchitectureEnd-to-End Omni-Modal Multimodal TransformerReal-time speech-to-speech multimodal transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.3/1M in) across full 33K windowFlat rate ($32/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.03/1M tokensAutomatic prefix caching at $3.2/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling
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) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)Text BPE (~4 chars/token) · Audio (~25–32 tokens/sec)
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 Modalitiestext, vision, audioaudio, text
Output Modalitiestext, audioaudio, text

Qwen-Omni Turbo vs GPT-Realtime-2.1: Jawaban Cepat (FAQ)

Which is more intelligent, Qwen-Omni Turbo or GPT-Realtime-2.1?

Qwen-Omni Turbo is more intelligent. It scores 74 compared with 65 on the composite Intelligence Index.

Which model is cheaper to run?

Qwen-Omni Turbo is cheaper at $0.20 per 1M tokens blended, compared with $15.04 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-Realtime-2.1 has lower latency, with a time to first token of 0.32s compared with 0.38s.

Which model has a larger context window?

GPT-Realtime-2.1 has a larger context window, supporting 128K tokens compared with 32.8K tokens.

Kesimpulan

Baik Qwen-Omni Turbo (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT-Realtime-2.1 (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Qwen-Omni Turbo unggul dalam penalaran dan pemrograman, Qwen-Omni Turbo memberikan kecepatan generasi token lebih tinggi, dan Qwen-Omni Turbo lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Qwen-Omni Turbo atau GPT-Realtime-2.1?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Qwen-Omni Turbo memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Qwen-Omni Turbo vs GPT-Realtime-2.1?+

Qwen-Omni Turbo mengenakan biaya $0.30 / $1.20 per 1M token input/output, sedangkan GPT-Realtime-2.1 sebesar $32.00 / $64.00. Secara keseluruhan, Qwen-Omni Turbo lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

Qwen-Omni Turbo mendukung konteks 32.8K token dibandingkan 128K token pada GPT-Realtime-2.1, sementara Qwen-Omni Turbo unggul dalam kecepatan output token per detik.

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.

Sumber resmi: Dokumentasi API resmi Alibaba & OpenAI serta evaluasi benchmark independen (2026).