Head-to-Head Model Comparison

Nemotron 3 Super 120B A12B vs Llama 3.1 405B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

Paylaş

İstediğiniz Modelleri Seçin ve Karşılaştırın

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Nemotron 3 Super 120B A12BProfile

Llama 3.1 405BProfile

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Popular Matchups:

NVIDIA

Nemotron 3 Super 120B A12B

Otonom Ajan ve Araç Modeli

NVIDIA tarafından geliştirilen Nemotron 3 Super 120B A12B; otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon için tasarlanmış olup 262K bağlam penceresi, 85 token/sn hız, 53/100 zeka indeksi ve 1M token başına $0.

Intelligence Index53 / 100

Input Token:

$0.30 / 1M

Output Token:

$0.80 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

51%

Llama 3.1 405B

Açık Ağırlıklı Temel Model

Meta tarafından geliştirilen Llama 3.1 405B; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 128K bağlam penceresi, 50 token/sn hız, 48/100 zeka indeksi ve ücretsiz açık ağırlık

Intelligence Index48 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

41.5%

Bir Bakışta Temel Farklar

Llama 3.1 405B is 1.1x cheaper for API usage (input + output tokens combined).
Nemotron 3 Super 120B A12B has a larger context window (262K vs 128K tokens).
Nemotron 3 Super 120B A12B is faster at 85 tok/s vs 50 tok/s.
Nemotron 3 Super 120B A12B leads on SWE-bench coding (51.0% vs 41.5%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Nemotron 3 Super 120B A12B	Llama 3.1 405B
Intelligence Index Composite reasoning & knowledge score (0-100)	53	48
Provider	NVIDIA	Meta
Input Price Cost per million input tokens	$0.30 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$0.80 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.18 / 1M	$0.53 / 1M
Context Window Maximum input + output tokens	262.1K tokens~393 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	33K	8K
Throughput Speed Tokens generated per second	85 tok/s	50 tok/s
SWE-bench Verified Real-world software engineering	51%	41.5%
GPQA Diamond Graduate-level reasoning	64.5%	53%
Cached Input Price Prompt caching discount per 1M tokens	$0.06 / 1M	$0.75 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework

Coding

Nemotron 3 Super 120B A12B

+9.5% SWE-bench lead

Cost

Llama 3.1 405B

1.1x cheaper monthly runtime

Speed

Nemotron 3 Super 120B A12B

+70% faster generation

Context

Nemotron 3 Super 120B A12B

262.1K tokens window

Doğrulanmış Benchmark Puanları

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

Nemotron 3 Super 120B A12BLlama 3.1 405B

SWE-bench Verified (Autonomous Coding)

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

51%vs41.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

64.5%vs53%

MMLU-Pro (Multi-task Language Understanding)

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

82.8%vs77.2%

LMSYS Chatbot Arena Elo

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

1350ptsvs1288pts

Terminal-Bench (Agentic Coding & Terminal Use)

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

45%vsN/A

AIME (Advanced Math Competition)

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

74%vsN/A

Long-Context Reasoning

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

82%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs50 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 Super 120B A12B0.46s

Llama 3.1 405B0.85s

Est. End-to-End Response (500 tokens)TTFT + generation time

Nemotron 3 Super 120B A12B6.34s

Llama 3.1 405B10.85s

Gerçek Zamanlı Token Maliyet Simülatörü

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Nemotron 3 Super 120B A12B Monthly API Bill

$1.26 / month

$0.3/1M in · $0.8/1M out

Llama 3.1 405B Monthly API Bill

$1.13 / month

$0/1M in · $0/1M out

Llama 3.1 405B saves approximately $0.14 / month (11%) under this workload.1.1x Savings

Nemotron 3 Super 120B A12B · Strengths & Key Advantages

262K bağlam penceresi ve yanıt başına maksimum 33K çıktı tokenı kapasitesi (SWE-bench Verified 51% · GPQA Diamond 64.5%)
Sadece 460 ms ilk token gecikmesi (TTFT) ile saniyede 85 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (120B (12B 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 3.1 405B · Strengths & Key Advantages

128K bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (SWE-bench Verified 41.5% · GPQA Diamond 53%)
Sadece 850 ms ilk token gecikmesi (TTFT) ile saniyede 50 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (405B)

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.

Metric	Nemotron 3 Super 120B A12B	Llama 3.1 405B
Cost per Task Estimated USD to finish one task	$0.38	$0.20
Output Tokens / Task Tokens generated per task	38K	24K
Reasoning Tokens / Task Thinking tokens burned per task	18K	0K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	Nemotron 3 Super 120B A12B	Llama 3.1 405B
Official API Model ID (SDK)	nemotron-3-super-120b-a12b	meta-llama/Llama-3.1-405B
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2026-03	2024-07
Knowledge Cutoff	January 2026	December 2023
Architecture	High-Throughput Sparse MoE (120B Total / 12B Active)	World’s Largest Open Foundation Transformer
Parameters	120B (12B active MoE)	405B
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 ($0.3/1M in) across full 262K window	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Cached input at $0.06/1M 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)	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	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)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 74 GB VRAM (4-bit Quantized) · 258 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 251 GB VRAM (4-bit Quantized) · 871 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
Output Modalities	text	text

Nemotron 3 Super 120B A12B vs Llama 3.1 405B: Hızlı Yanıtlar (SSS)

Which is more intelligent, Nemotron 3 Super 120B A12B or Llama 3.1 405B?

Nemotron 3 Super 120B A12B is more intelligent. It scores 53 compared with 48 on the composite Intelligence Index.

Which model is faster?

Nemotron 3 Super 120B A12B is faster, generating 85 tokens per second compared with 50 tokens per second.

Which model is cheaper to run?

Nemotron 3 Super 120B A12B is cheaper at $0.18 per 1M tokens blended, compared with $0.53 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nemotron 3 Super 120B A12B has lower latency, with a time to first token of 0.46s compared with 0.85s.

Which model has a larger context window?

Nemotron 3 Super 120B A12B has a larger context window, supporting 262.1K tokens compared with 128K tokens.

Sonuç

Hem Nemotron 3 Super 120B A12B (otonom ajan iş akışları, araç çağırma (tool calling) ve çok adımlı otomasyon, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de Llama 3.1 405B (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: Nemotron 3 Super 120B A12B karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Nemotron 3 Super 120B A12B daha yüksek üretim hızı sağlar; Nemotron 3 Super 120B A12B ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Nemotron 3 Super 120B A12B mi yoksa Llama 3.1 405B mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Nemotron 3 Super 120B A12B önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Nemotron 3 Super 120B A12B ve Llama 3.1 405B API fiyatları nasıl karşılaştırılır?+

Nemotron 3 Super 120B A12B 1M giriş/çıkış tokeni başına $0.30 / $0.80 ücretlendirilirken, Llama 3.1 405B $0.00 / $0.00 seviyesindedir. Karma maliyette Nemotron 3 Super 120B A12B daha avantajlıdır.

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

Nemotron 3 Super 120B A12B 262.1K token bağlam penceresi sunarken Llama 3.1 405B 128K token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Nemotron 3 Super 120B A12B 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.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Nemotron 3 Super 120B A12B vs Llama 3.1 405B

İstediğiniz Modelleri Seçin ve Karşılaştırın

Nemotron 3 Super 120B A12B

Llama 3.1 405B

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

Nemotron 3 Super 120B A12B · Strengths & Key Advantages

Considerations & Trade-offs

Llama 3.1 405B · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

Nemotron 3 Super 120B A12B vs Llama 3.1 405B: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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