Qwen3-VL Plus vs QwQ Plus
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Qwen3-VL Plus dari Alibaba dan QwQ Plus dari Alibaba adalah dua model AI unggulan. Qwen3-VL Plus menawarkan jendela konteks 262.1K token dengan harga $0.50/$2.00 per 1 juta token, sedangkan QwQ Plus menyediakan konteks 131.1K token seharga $0.40/$1.60 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Qwen3-VL Plus
AI Multimodal AsliQwen3-VL Plus dari Alibaba adalah model AI yang dirancang untuk pemahaman multimodal asli (teks & visual) serta analisis dokumen kompleks, menghadirkan jendela konteks 262K, kecepatan 80 token/detik, indeks kecerdasan 82/100, serta tarif $0
$0.50 / 1M
$2.00 / 1M
262.1K tokens
N/A
QwQ Plus
Mesin Penalaran MendalamQwQ Plus dari Alibaba adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 131K, kecepatan 70 token/detik, indeks kecerdasan 84/100, serta tarif $0.4/$1.
$0.40 / 1M
$1.60 / 1M
131.1K tokens
45%
Perbedaan Utama Sekilas
- QwQ Plus is 1.2x cheaper for API usage (input + output tokens combined).
- Qwen3-VL Plus has a larger context window (262K vs 131K tokens).
- Qwen3-VL Plus is faster at 80 tok/s vs 70 tok/s.
| Feature | Qwen3-VL Plus | QwQ Plus |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 82 | 84 |
Provider | Alibaba | Alibaba |
Input Price Cost per million input tokens | $0.50 / 1M | $0.40 / 1M |
Output Price Cost per million output tokens | $2.00 / 1M | $1.60 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.34 / 1M | $0.27 / 1M |
Context Window Maximum input + output tokens | 262.1K tokens~393 A4 pages of text | 131.1K tokens~197 A4 pages of text |
Max Output Tokens Per single request | 16K | 16K |
Throughput Speed Tokens generated per second | 80 tok/s | 70 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 45% |
GPQA Diamond Graduate-level reasoning | 64% | 65.2% |
Cached Input Price Prompt caching discount per 1M tokens | $0.05 / 1M | $0.04 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkEvaluations ongoing
Skor Benchmark Terverifikasi
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Tokens emitted per second during active generation streaming.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Qwen3-VL Plus · Strengths & Key Advantages
- Jendela konteks 262K dengan kapasitas output maksimum hingga 16K token (GPQA Diamond 64% · MMLU-Pro 81%)
- Kecepatan generasi tinggi 80 token/detik dengan latensi token pertama (TTFT) hanya 560 ms
- Skema harga API kompetitif (tarif $0.5/$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
QwQ Plus · Strengths & Key Advantages
- Jendela konteks 131K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 45% · GPQA Diamond 65.2%)
- Kecepatan generasi tinggi 70 token/detik dengan latensi token pertama (TTFT) hanya 850 ms
- Skema harga API kompetitif (tarif $0.4/$1.6 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Qwen3-VL Plus | QwQ Plus |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.16 | $0.12 |
Output Tokens / Task Tokens generated per task | 20K | 24K |
Reasoning Tokens / Task Thinking tokens burned per task | 6K | 14K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Qwen3-VL Plus | QwQ Plus |
|---|---|---|
| Official API Model ID (SDK) | qwen3-vl-plus-instruct | qwq-plus-instruct |
| API Protocol | Alibaba REST API (OpenAI-Compatible) | Alibaba REST API (OpenAI-Compatible) |
| Release Date | 2025-09 | 2025-03 |
| Knowledge Cutoff | July 2025 | January 2025 |
| Architecture | Multimodal Vision-Language Frontier Transformer | Deep Reasoning Chain-of-Thought Transformer |
| Parameters | Confidential | 32B (Distilled Reasoning Engine) |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.5/1M in) across full 262K window | Flat rate ($0.4/1M in) across full 131K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Cached input at $0.04/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | Cloud-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 Classification | Alibaba Production Safety & Alignment Verified | Alibaba Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text |
| Output Modalities | text | text |
Qwen3-VL Plus vs QwQ Plus: Jawaban Cepat (FAQ)
Which is more intelligent, Qwen3-VL Plus or QwQ Plus?
QwQ Plus is more intelligent. It scores 84 compared with 82 on the composite Intelligence Index.
Which model is faster?
Qwen3-VL Plus is faster, generating 80 tokens per second compared with 70 tokens per second.
Which model is cheaper to run?
QwQ Plus is cheaper at $0.27 per 1M tokens blended, compared with $0.34 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Qwen3-VL Plus has lower latency, with a time to first token of 0.56s compared with 0.85s.
Which model has a larger context window?
Qwen3-VL Plus has a larger context window, supporting 262.1K tokens compared with 131.1K tokens.
Kesimpulan
Baik Qwen3-VL Plus (Sangat cocok untuk pemahaman multimodal asli (teks & visual) serta analisis dokumen kompleks, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun QwQ Plus (Sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: QwQ Plus unggul dalam penalaran dan pemrograman, Qwen3-VL Plus memberikan kecepatan generasi token lebih tinggi, dan QwQ Plus lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Qwen3-VL Plus atau QwQ Plus?+
Dalam indeks kecerdasan gabungan dan benchmark coding, QwQ Plus memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Qwen3-VL Plus vs QwQ Plus?+
Qwen3-VL Plus mengenakan biaya $0.50 / $2.00 per 1M token input/output, sedangkan QwQ Plus sebesar $0.40 / $1.60. Secara keseluruhan, QwQ Plus lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Qwen3-VL Plus mendukung konteks 262.1K token dibandingkan 131.1K token pada QwQ Plus, sementara Qwen3-VL Plus unggul dalam kecepatan output token per detik.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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 & Alibaba serta evaluasi benchmark independen (2026).