Nemotron 3 Ultra 550B A55B vs Qwen3.8 Max Preview
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Nemotron 3 Ultra 550B A55B dari NVIDIA dan Qwen3.8 Max Preview dari Alibaba adalah dua model AI unggulan. Nemotron 3 Ultra 550B A55B menawarkan jendela konteks 1M token dengan harga $1.00/$3.00 per 1 juta token, sedangkan Qwen3.8 Max Preview menyediakan konteks 1M token seharga $0.00/$0.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
Ganti & Bandingkan Model Apa Saja
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Nemotron 3 Ultra 550B A55B
Model Dasar Bobot TerbukaNemotron 3 Ultra 550B A55B dari NVIDIA adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 1M, kecepatan 65 token/detik, indeks kecerdasan 60/100, serta t
$1.00 / 1M
$3.00 / 1M
1M tokens
64.5%
Qwen3.8 Max Preview
Model Dasar Bobot TerbukaQwen3.8 Max Preview dari Alibaba adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 1M, kecepatan 60 token/detik, indeks kecerdasan 93/100, serta akses g
$0.00 / 1M
$0.00 / 1M
1M tokens
75.2%
Perbedaan Utama Sekilas
- Qwen3.8 Max Preview is 1.0x cheaper for API usage (input + output tokens combined).
- Nemotron 3 Ultra 550B A55B is faster at 65 tok/s vs 60 tok/s.
- Qwen3.8 Max Preview leads on SWE-bench coding (75.2% vs 64.5%).
| Feature | Nemotron 3 Ultra 550B A55B | Qwen3.8 Max Preview |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 60 | 93 |
Provider | NVIDIA | Alibaba |
Input Price Cost per million input tokens | $1.00 / 1M | $0.00 / 1M |
Output Price Cost per million output tokens | $3.00 / 1M | $0.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.68 / 1M | $0.00 / 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 | 66K | 32K |
Throughput Speed Tokens generated per second | 65 tok/s | 60 tok/s |
SWE-bench Verified Real-world software engineering | 64.5% | 75.2% |
GPQA Diamond Graduate-level reasoning | 76% | 79.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.25 / 1M | $0.00 / 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.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
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.
Nemotron 3 Ultra 550B A55B · Strengths & Key Advantages
- Jendela konteks 1M dengan kapasitas output maksimum hingga 66K token (SWE-bench Verified 64.5% · GPQA Diamond 76%)
- Kecepatan generasi tinggi 65 token/detik dengan latensi token pertama (TTFT) hanya 620 ms
- Bobot terbuka (550B (55B MoE)) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Qwen3.8 Max Preview · Strengths & Key Advantages
- Jendela konteks 1M dengan kapasitas output maksimum hingga 32K token (SWE-bench Verified 75.2% · GPQA Diamond 79.5%)
- Kecepatan generasi tinggi 60 token/detik dengan latensi token pertama (TTFT) hanya 680 ms
- Bobot terbuka (2.4T total (95B MoE)) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- 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 | Nemotron 3 Ultra 550B A55B | Qwen3.8 Max Preview |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.85 | $0.00 |
Output Tokens / Task Tokens generated per task | 48K | 35K |
Reasoning Tokens / Task Thinking tokens burned per task | 24K | 15K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Nemotron 3 Ultra 550B A55B | Qwen3.8 Max Preview |
|---|---|---|
| Official API Model ID (SDK) | nemotron-3-ultra-550b-a55b | qwen3-8-max-preview-instruct |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-06 | 2026-07 |
| Knowledge Cutoff | February 2026 | April 2026 |
| Architecture | Colossal Sparse MoE (550B Total / 55B Active) | Colossus-Scale Open Sparse Mixture-of-Experts |
| Parameters | 550B (55B active MoE) | 2.4T total (95B active MoE) |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($1/1M in) across full 1000K window | Free across full context window (only KV-cache VRAM scales) |
| Prompt Cache Policy & TTL | Cached input at $0.25/1M tokens | Automatic prefix KV-caching in vLLM / SGLang (0 cost) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 341 GB VRAM (4-bit Quantized) · 1183 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 1488 GB VRAM (4-bit Quantized) · 5160 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text | text, vision |
| Output Modalities | text | text |
Nemotron 3 Ultra 550B A55B vs Qwen3.8 Max Preview: Jawaban Cepat (FAQ)
Which is more intelligent, Nemotron 3 Ultra 550B A55B or Qwen3.8 Max Preview?
Qwen3.8 Max Preview is more intelligent. It scores 93 compared with 60 on the composite Intelligence Index.
Which model is faster?
Nemotron 3 Ultra 550B A55B is faster, generating 65 tokens per second compared with 60 tokens per second.
Which model is cheaper to run?
Qwen3.8 Max Preview is cheaper at $0.00 per 1M tokens blended, compared with $0.68 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nemotron 3 Ultra 550B A55B has lower latency, with a time to first token of 0.62s compared with 0.68s.
Kesimpulan
Baik Nemotron 3 Ultra 550B A55B (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Qwen3.8 Max Preview (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Qwen3.8 Max Preview unggul dalam penalaran dan pemrograman, Nemotron 3 Ultra 550B A55B memberikan kecepatan generasi token lebih tinggi, dan Qwen3.8 Max Preview lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Nemotron 3 Ultra 550B A55B atau Qwen3.8 Max Preview?+
Dalam indeks kecerdasan gabungan dan benchmark coding, Qwen3.8 Max Preview memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Nemotron 3 Ultra 550B A55B vs Qwen3.8 Max Preview?+
Nemotron 3 Ultra 550B A55B mengenakan biaya $1.00 / $3.00 per 1M token input/output, sedangkan Qwen3.8 Max Preview sebesar $0.00 / $0.00. Secara keseluruhan, Qwen3.8 Max Preview lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Nemotron 3 Ultra 550B A55B mendukung konteks 1M token dibandingkan 1M token pada Qwen3.8 Max Preview, sementara Nemotron 3 Ultra 550B A55B 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.
Related reading
- Command A Plus vs Nemotron 3 Ultra 550B A55B: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Llama 4 Behemoth vs Nemotron 3 Ultra 550B A55B: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Llama 5 vs Qwen3.8 Max Preview: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Nemotron 3 Ultra 550B A55B vs Gemini 4 Argon: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Nemotron 3 Ultra 550B A55B vs GPT-OSS 120B: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Nemotron 3 Ultra 550B A55B vs Llama 5: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
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 NVIDIA & Alibaba serta evaluasi benchmark independen (2026).