Head-to-Head Model Comparison

Nemotron 3 Ultra 550B A55B vs Llama 5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Nemotron 3 Ultra 550B A55B vs Llama 5: Benchmarks, Pricing & Speed Comparison

NVIDIA tarafından geliştirilen Nemotron 3 Ultra 550B A55B ve Meta tarafından sunulan Llama 5, kendi sınıflarının öne çıkan yapay zeka modelleridir. Nemotron 3 Ultra 550B A55B, 1M token bağlam penceresi ve 1M token başına $1.00/$3.00 fiyat sunarken; Llama 5, 5M token bağlam penceresi ve $0.00/$0.00 fiyatla gelir. Aşağıda tüm benchmark, hız ve maliyet detaylarını inceleyebilirsiniz.

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NVIDIA

Nemotron 3 Ultra 550B A55B

Açık Ağırlıklı Temel Model

NVIDIA tarafından geliştirilen Nemotron 3 Ultra 550B A55B; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 1M bağlam penceresi, 65 token/sn hız, 60/100 zeka indeksi ve 1M token b

Intelligence Index60 / 100
Input Token:

$1.00 / 1M

Output Token:

$3.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

64.5%

Meta

Llama 5

Açık Ağırlıklı Temel Model

Meta tarafından geliştirilen Llama 5; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 5M bağlam penceresi, 65 token/sn hız, 94/100 zeka indeksi ve ücretsiz açık ağırlık erişimi s

Intelligence Index94 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

5M tokens

SWE-bench Verified:

74%

Bir Bakışta Temel Farklar

  • Llama 5 is 1.0x cheaper for API usage (input + output tokens combined).
  • Llama 5 has a larger context window (5M vs 1M tokens).
  • Llama 5 is faster at 65 tok/s vs 65 tok/s.
  • Llama 5 leads on SWE-bench coding (74.0% vs 64.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNemotron 3 Ultra 550B A55BLlama 5
Intelligence Index
Composite reasoning & knowledge score (0-100)
6094
Provider
NVIDIAMeta
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 text5M tokens~7,500 A4 pages of text
Max Output Tokens
Per single request
66K128K
Throughput Speed
Tokens generated per second
65 tok/s65 tok/s
SWE-bench Verified
Real-world software engineering
64.5%74%
GPQA Diamond
Graduate-level reasoning
76%84%
Cached Input Price
Prompt caching discount per 1M tokens
$0.25 / 1M$0.00 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework
Coding
Llama 5
+9.5% SWE-bench lead
Cost
Llama 5
1.0x cheaper monthly runtime
Speed
Llama 5
+0% faster generation
Context
Llama 5
5M tokens window

Doğrulanmış Benchmark Puanları

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

Nemotron 3 Ultra 550B A55BLlama 5
SWE-bench Verified (Autonomous Coding)

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

64.5%vs74%
GPQA Diamond (Doctorate-Level Science & Math)

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

76%vs84%
MMLU-Pro (Multi-task Language Understanding)

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

87.5%vs87%
LMSYS Chatbot Arena Elo

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

1425ptsvs1485pts
Terminal-Bench (Agentic Coding & Terminal Use)

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

53%vsN/A
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs68%
AIME (Advanced Math Competition)

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

86%vs88%
Long-Context Reasoning

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

89%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

65 tok/s vs65 tok/s

Gecikme Süresi ve Yanıt Hızı

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
Nemotron 3 Ultra 550B A55B0.62s
Llama 50.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nemotron 3 Ultra 550B A55B8.31s
Llama 58.54s

Gerçek Zamanlı Token Maliyet Simülatörü

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)
Nemotron 3 Ultra 550B A55B Monthly API Bill
$4.58 / month
$1/1M in · $3/1M out
Llama 5 Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Llama 5 saves approximately $4.58 / month (100%) under this workload.1.0x Savings

Nemotron 3 Ultra 550B A55B · Strengths & Key Advantages

  • 1M bağlam penceresi ve yanıt başına maksimum 66K çıktı tokenı kapasitesi (SWE-bench Verified 64.5% · GPQA Diamond 76%)
  • Sadece 620 ms ilk token gecikmesi (TTFT) ile saniyede 65 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (550B (55B MoE))
Considerations & Trade-offs
  • Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
  • Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Llama 5 · Strengths & Key Advantages

  • 5M bağlam penceresi ve yanıt başına maksimum 128K çıktı tokenı kapasitesi (SWE-bench Verified 74% · GPQA Diamond 84%)
  • Sadece 850 ms ilk token gecikmesi (TTFT) ile saniyede 65 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (600B+ total (~40-80B ))
Considerations & Trade-offs
  • Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
  • Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Token Use & Task Economics

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

MetricNemotron 3 Ultra 550B A55BLlama 5
Cost per Task
Estimated USD to finish one task
$0.85$0.00
Output Tokens / Task
Tokens generated per task
48K40K
Reasoning Tokens / Task
Thinking tokens burned per task
24K20K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

FeatureNemotron 3 Ultra 550B A55BLlama 5
Official API Model ID (SDK)nemotron-3-ultra-550b-a55bmeta-llama/Llama-5
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2026-062026-04
Knowledge CutoffFebruary 2026January 2026
ArchitectureColossal Sparse MoE (550B Total / 55B Active)Mixture-of-Experts with recursive self-improvement (~600B total, 40-80B active)
Parameters550B (55B active MoE)600B+ total (~40-80B active)
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (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 windowFree across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTLCached input at $0.25/1M tokensAutomatic prefix KV-caching in vLLM / SGLang (0 cost)
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 toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull 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 BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
Quantization & Min GPU VRAMBF16 / 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) · 372 GB VRAM (4-bit Quantized) · 1290 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-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 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext, vision, video, audio
Output Modalitiestexttext

Nemotron 3 Ultra 550B A55B vs Llama 5: Hızlı Yanıtlar (SSS)

Which is more intelligent, Nemotron 3 Ultra 550B A55B or Llama 5?

Llama 5 is more intelligent. It scores 94 compared with 60 on the composite Intelligence Index.

Which model is cheaper to run?

Llama 5 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 0.85s.

Which model has a larger context window?

Llama 5 has a larger context window, supporting 5M tokens compared with 1M tokens.

Sonuç

Hem Nemotron 3 Ultra 550B A55B (özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de Llama 5 (özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Llama 5 karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Nemotron 3 Ultra 550B A55B daha yüksek üretim hızı sağlar; Llama 5 ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Nemotron 3 Ultra 550B A55B mi yoksa Llama 5 mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Llama 5 önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Nemotron 3 Ultra 550B A55B ve Llama 5 API fiyatları nasıl karşılaştırılır?+

Nemotron 3 Ultra 550B A55B 1M giriş/çıkış tokeni başına $1.00 / $3.00 ücretlendirilirken, Llama 5 $0.00 / $0.00 seviyesindedir. Karma maliyette Llama 5 daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

Nemotron 3 Ultra 550B A55B 1M token bağlam penceresi sunarken Llama 5 5M token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Nemotron 3 Ultra 550B A55B öndedir.

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.

Resmi kaynaklar: NVIDIA ve Meta resmi API dokümantasyonu, sistem kartları ve bağımsız benchmark testleri (2026).