Qwen3.7 Plus vs Qwen3.7 Max
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Qwen3.7 Plus dari Alibaba dan Qwen3.7 Max dari Alibaba adalah dua model AI unggulan. Qwen3.7 Plus menawarkan jendela konteks 1M token dengan harga $0.80/$3.20 per 1 juta token, sedangkan Qwen3.7 Max menyediakan konteks 1M token seharga $1.80/$7.20 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Qwen3.7 Plus
Model Unggulan Garis DepanQwen3.7 Plus dari Alibaba adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 1M, kecepatan 92 token/detik, indeks kecerdasan 89/100, serta tarif $
$0.80 / 1M
$3.20 / 1M
1M tokens
68%
Qwen3.7 Max
Model Agen Otonom & AlatQwen3.7 Max dari Alibaba adalah model AI yang dirancang untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, menghadirkan jendela konteks 1M, kecepatan 80 token/detik, indeks kecerdasan 92/100, serta
$1.80 / 1M
$7.20 / 1M
1M tokens
73.5%
Perbedaan Utama Sekilas
- Qwen3.7 Plus is 2.2x cheaper for API usage (input + output tokens combined).
- Qwen3.7 Plus is faster at 92 tok/s vs 80 tok/s.
- Qwen3.7 Max leads on SWE-bench coding (73.5% vs 68.0%).
| Feature | Qwen3.7 Plus | Qwen3.7 Max |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 89 | 92 |
Provider | Alibaba | Alibaba |
Input Price Cost per million input tokens | $0.80 / 1M | $1.80 / 1M |
Output Price Cost per million output tokens | $3.20 / 1M | $7.20 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.54 / 1M | $1.21 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 16K | 32K |
Throughput Speed Tokens generated per second | 92 tok/s | 80 tok/s |
SWE-bench Verified Real-world software engineering | 68% | 73.5% |
GPQA Diamond Graduate-level reasoning | 75% | 78.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.08 / 1M | $0.18 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor 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.
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.
Qwen3.7 Plus · Strengths & Key Advantages
- Jendela konteks 1M dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 68% · GPQA Diamond 75%)
- Kecepatan generasi tinggi 92 token/detik dengan latensi token pertama (TTFT) hanya 440 ms
- Skema harga API kompetitif (tarif $0.8/$3.2 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
Qwen3.7 Max · Strengths & Key Advantages
- Jendela konteks 1M dengan kapasitas output maksimum hingga 32K token (SWE-bench Verified 73.5% · GPQA Diamond 78.5%)
- Kecepatan generasi tinggi 80 token/detik dengan latensi token pertama (TTFT) hanya 580 ms
- Skema harga API kompetitif (tarif $1.8/$7.2 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Qwen3.7 Plus | Qwen3.7 Max |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.24 | $0.38 |
Output Tokens / Task Tokens generated per task | 26K | 32K |
Reasoning Tokens / Task Thinking tokens burned per task | 9K | 14K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Qwen3.7 Plus | Qwen3.7 Max |
|---|---|---|
| Official API Model ID (SDK) | qwen3-7-plus-instruct | qwen3-7-max-instruct |
| API Protocol | Alibaba REST API (OpenAI-Compatible) | Alibaba REST API (OpenAI-Compatible) |
| Release Date | 2026-06 | 2026-05 |
| Knowledge Cutoff | April 2026 | April 2026 |
| Architecture | High-Value Multimodal Foundation Transformer | Next-Generation Deep Frontier Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.8/1M in) across full 1000K window | Flat rate ($1.8/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Cached input at $0.08/1M tokens | Cached input at $0.18/1M 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 |
Qwen3.7 Plus vs Qwen3.7 Max: Jawaban Cepat (FAQ)
Which is more intelligent, Qwen3.7 Plus or Qwen3.7 Max?
Qwen3.7 Max is more intelligent. It scores 92 compared with 89 on the composite Intelligence Index.
Which model is faster?
Qwen3.7 Plus is faster, generating 92 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
Qwen3.7 Plus is cheaper at $0.54 per 1M tokens blended, compared with $1.21 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Qwen3.7 Plus has lower latency, with a time to first token of 0.44s compared with 0.58s.
Kesimpulan
Baik Qwen3.7 Plus (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Qwen3.7 Max (Sangat cocok untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Qwen3.7 Max unggul dalam penalaran dan pemrograman, Qwen3.7 Plus memberikan kecepatan generasi token lebih tinggi, dan Qwen3.7 Plus lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Qwen3.7 Plus atau Qwen3.7 Max?+
Dalam indeks kecerdasan gabungan dan benchmark coding, Qwen3.7 Max memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Qwen3.7 Plus vs Qwen3.7 Max?+
Qwen3.7 Plus mengenakan biaya $0.80 / $3.20 per 1M token input/output, sedangkan Qwen3.7 Max sebesar $1.80 / $7.20. Secara keseluruhan, Qwen3.7 Plus lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Qwen3.7 Plus mendukung konteks 1M token dibandingkan 1M token pada Qwen3.7 Max, sementara Qwen3.7 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).