Head-to-Head Model Comparison

Llama 3.1 Nemotron Ultra 253B vs DeepSeek-R1-0528

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
Llama 3.1 Nemotron Ultra 253B vs DeepSeek-R1-0528: Benchmarks, Pricing & Speed Comparison

NVIDIA tarafından geliştirilen Llama 3.1 Nemotron Ultra 253B ve DeepSeek tarafından sunulan DeepSeek-R1-0528, kendi sınıflarının öne çıkan yapay zeka modelleridir. Llama 3.1 Nemotron Ultra 253B, 128K token bağlam penceresi ve 1M token başına $0.80/$2.40 fiyat sunarken; DeepSeek-R1-0528, 128K token bağlam penceresi ve $0.55/$2.19 fiyatla gelir. Aşağıda tüm benchmark, hız ve maliyet detaylarını inceleyebilirsiniz.

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NVIDIA

Llama 3.1 Nemotron Ultra 253B

Açık Ağırlıklı Temel Model

NVIDIA tarafından geliştirilen Llama 3.1 Nemotron Ultra 253B; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 128K bağlam penceresi, 60 token/sn hız, 54/100 zeka indeksi ve 1M to

Intelligence Index54 / 100
Input Token:

$0.80 / 1M

Output Token:

$2.40 / 1M

Context Window:

128K tokens

SWE-bench Verified:

52.8%

DeepSeek

DeepSeek-R1-0528

Açık Ağırlıklı Akıl Yürütme

DeepSeek tarafından geliştirilen DeepSeek-R1-0528; yüksek verimli açık ağırlıklı düşünce zinciri (Chain-of-Thought) akıl yürütme için tasarlanmış olup 128K bağlam penceresi, 48 token/sn hız, 52/100 zeka indeksi ve 1M token başına $0.55/$2.1

Intelligence Index52 / 100
Input Token:

$0.55 / 1M

Output Token:

$2.19 / 1M

Context Window:

128K tokens

SWE-bench Verified:

51.8%

Bir Bakışta Temel Farklar

  • DeepSeek-R1-0528 is 1.2x cheaper for API usage (input + output tokens combined).
  • Llama 3.1 Nemotron Ultra 253B is faster at 60 tok/s vs 48 tok/s.
  • Llama 3.1 Nemotron Ultra 253B leads on SWE-bench coding (52.8% vs 51.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureLlama 3.1 Nemotron Ultra 253BDeepSeek-R1-0528
Intelligence Index
Composite reasoning & knowledge score (0-100)
5452
Provider
NVIDIADeepSeek
Input Price
Cost per million input tokens
$0.80 / 1M$0.55 / 1M
Output Price
Cost per million output tokens
$2.40 / 1M$2.19 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.54 / 1M$0.43 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
16K8K
Throughput Speed
Tokens generated per second
60 tok/s48 tok/s
SWE-bench Verified
Real-world software engineering
52.8%51.8%
GPQA Diamond
Graduate-level reasoning
66%74.2%
Cached Input Price
Prompt caching discount per 1M tokens
$0.20 / 1M$0.14 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework
Coding
Llama 3.1 Nemotron Ultra 253B
+1.0% SWE-bench lead
Cost
DeepSeek-R1-0528
1.2x cheaper monthly runtime
Speed
Llama 3.1 Nemotron Ultra 253B
+25% faster generation
Context
Tied
128K tokens window

Doğrulanmış Benchmark Puanları

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

Llama 3.1 Nemotron Ultra 253BDeepSeek-R1-0528
SWE-bench Verified (Autonomous Coding)

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

52.8%vs51.8%
GPQA Diamond (Doctorate-Level Science & Math)

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

66%vs74.2%
MMLU-Pro (Multi-task Language Understanding)

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

84%vs85.6%
LMSYS Chatbot Arena Elo

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

1362ptsvs1355pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs12%
Terminal-Bench (Agentic Coding & Terminal Use)

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

46.5%vs34%
SciCode (Scientific Computing)

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

N/Avs31.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs54%
AIME (Advanced Math Competition)

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

76%vs85%
Long-Context Reasoning

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

82%vs78%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

60 tok/s vs48 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
Llama 3.1 Nemotron Ultra 253B0.60s
DeepSeek-R1-05280.90s
Est. End-to-End Response (500 tokens)TTFT + generation time
Llama 3.1 Nemotron Ultra 253B8.93s
DeepSeek-R1-052811.32s

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)
Llama 3.1 Nemotron Ultra 253B Monthly API Bill
$3.66 / month
$0.8/1M in · $2.4/1M out
DeepSeek-R1-0528 Monthly API Bill
$3.01 / month
$0.55/1M in · $2.19/1M out
DeepSeek-R1-0528 saves approximately $0.65 / month (18%) under this workload.1.2x Savings

Llama 3.1 Nemotron Ultra 253B · Strengths & Key Advantages

  • 128K bağlam penceresi ve yanıt başına maksimum 16K çıktı tokenı kapasitesi (SWE-bench Verified 52.8% · GPQA Diamond 66%)
  • Sadece 600 ms ilk token gecikmesi (TTFT) ile saniyede 60 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (253B)
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

DeepSeek-R1-0528 · Strengths & Key Advantages

  • 128K bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (SWE-bench Verified 51.8% · GPQA Diamond 74.2%)
  • Sadece 900 ms ilk token gecikmesi (TTFT) ile saniyede 48 token yüksek üretim hızı
  • vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (671B (37B 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

Token Use & Task Economics

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

MetricLlama 3.1 Nemotron Ultra 253BDeepSeek-R1-0528
Cost per Task
Estimated USD to finish one task
$0.65$0.62
Output Tokens / Task
Tokens generated per task
42K45K
Reasoning Tokens / Task
Thinking tokens burned per task
20K25K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

FeatureLlama 3.1 Nemotron Ultra 253BDeepSeek-R1-0528
Official API Model ID (SDK)llama-3-1-nemotron-ultra-253bdeepseek-reasoner
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2025-042025-05
Knowledge CutoffDecember 2024March 2025
ArchitectureHigh-Throughput Aligned Frontier MoEOpen-Weights Reasoning MoE
Parameters253B671B (37B active MoE)
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 ($0.8/1M in) across full 128K windowFlat rate ($0.55/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.2/1M tokensAutomatic prefix caching at $0.14/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)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 · 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)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 157 GB VRAM (4-bit Quantized) · 544 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 416 GB VRAM (4-bit Quantized) · 1443 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
Output Modalitiestexttext

Llama 3.1 Nemotron Ultra 253B vs DeepSeek-R1-0528: Hızlı Yanıtlar (SSS)

Which is more intelligent, Llama 3.1 Nemotron Ultra 253B or DeepSeek-R1-0528?

Llama 3.1 Nemotron Ultra 253B is more intelligent. It scores 54 compared with 52 on the composite Intelligence Index.

Which model is faster?

Llama 3.1 Nemotron Ultra 253B is faster, generating 60 tokens per second compared with 48 tokens per second.

Which model is cheaper to run?

DeepSeek-R1-0528 is cheaper at $0.43 per 1M tokens blended, compared with $0.54 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Llama 3.1 Nemotron Ultra 253B has lower latency, with a time to first token of 0.60s compared with 0.90s.

Sonuç

Hem Llama 3.1 Nemotron Ultra 253B (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 DeepSeek-R1-0528 (yüksek verimli açık ağırlıklı düşünce zinciri (Chain-of-Thought) akıl yürütme, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Llama 3.1 Nemotron Ultra 253B karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Llama 3.1 Nemotron Ultra 253B daha yüksek üretim hızı sağlar; DeepSeek-R1-0528 ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Llama 3.1 Nemotron Ultra 253B mi yoksa DeepSeek-R1-0528 mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Llama 3.1 Nemotron Ultra 253B önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Llama 3.1 Nemotron Ultra 253B ve DeepSeek-R1-0528 API fiyatları nasıl karşılaştırılır?+

Llama 3.1 Nemotron Ultra 253B 1M giriş/çıkış tokeni başına $0.80 / $2.40 ücretlendirilirken, DeepSeek-R1-0528 $0.55 / $2.19 seviyesindedir. Karma maliyette DeepSeek-R1-0528 daha avantajlıdır.

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

Llama 3.1 Nemotron Ultra 253B 128K token bağlam penceresi sunarken DeepSeek-R1-0528 128K token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Llama 3.1 Nemotron Ultra 253B 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 DeepSeek resmi API dokümantasyonu, sistem kartları ve bağımsız benchmark testleri (2026).