Head-to-Head Model Comparison

GPT OSS Safeguard 120B vs Llama 3.1 Nemotron Safety Guard 8B v3

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial

Cambia y Compara Cualquier Modelo

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

GPT OSS Safeguard 120BProfile

Llama 3.1 Nemotron Safety Guard 8B v3Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT OSS Safeguard 120B

Modelo Base de Pesos Abiertos

GPT OSS Safeguard 120B de OpenAI es un modelo de IA diseñado para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, con ventana de contexto de 131K, velocidad de 90 tokens/s, índice de inteligencia de 52

Intelligence Index52 / 100

Input Token:

$0.15 / 1M

Output Token:

$0.60 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

41%

NVIDIA

Llama 3.1 Nemotron Safety Guard 8B v3

Modelo Base de Pesos Abiertos

Llama 3.1 Nemotron Safety Guard 8B v3 de NVIDIA es un modelo de IA diseñado para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, con ventana de contexto de 128K, velocidad de 180 tokens/s, índice de in

Intelligence Index36 / 100

Input Token:

$0.05 / 1M

Output Token:

$0.10 / 1M

Context Window:

128K tokens

SWE-bench Verified:

N/A

Diferencias Clave de un Vistazo

Llama 3.1 Nemotron Safety Guard 8B v3 is 4.4x cheaper for API usage (input + output tokens combined).
GPT OSS Safeguard 120B has a larger context window (131K vs 128K tokens).
Llama 3.1 Nemotron Safety Guard 8B v3 is faster at 180 tok/s vs 90 tok/s.

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

Característica	GPT OSS Safeguard 120B	Llama 3.1 Nemotron Safety Guard 8B v3
Intelligence Index Composite reasoning & knowledge score (0-100)	52	36
Provider	OpenAI	NVIDIA
Input Price Cost per million input tokens	$0.15 / 1M	$0.05 / 1M
Output Price Cost per million output tokens	$0.60 / 1M	$0.10 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.10 / 1M	$0.03 / 1M
Context Window Maximum input + output tokens	131.1K tokens~197 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	33K	2K
Throughput Speed Tokens generated per second	90 tok/s	180 tok/s
SWE-bench Verified Real-world software engineering	41%	N/A
GPQA Diamond Graduate-level reasoning	65%	N/A
Cached Input Price Prompt caching discount per 1M tokens	$0.01 / 1M	$0.01 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

Evaluations ongoing

Costo

Llama 3.1 Nemotron Safety Guard 8B v3

4.4x cheaper monthly runtime

Velocidad

Llama 3.1 Nemotron Safety Guard 8B v3

+100% faster generation

Contexto

GPT OSS Safeguard 120B

131.1K tokens window

Puntuaciones de Benchmarks Verificadas

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

GPT OSS Safeguard 120BLlama 3.1 Nemotron Safety Guard 8B v3

SWE-bench Verified (Autonomous Coding)

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

41%vsN/A

GPQA Diamond (Doctorate-Level Science & Math)

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

65%vsN/A

MMLU-Pro (Multi-task Language Understanding)

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

79%vsN/A

LMSYS Chatbot Arena Elo

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

1322ptsvs1160pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

9.2%vsN/A

Terminal-Bench (Agentic Coding & Terminal Use)

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

28%vsN/A

SciCode (Scientific Computing)

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

31%vsN/A

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

55%vsN/A

AIME (Advanced Math Competition)

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

82%vsN/A

Long-Context Reasoning

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

69.5%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

90 tok/s vs180 tok/s

Latencia y Tiempo de Respuesta

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

GPT OSS Safeguard 120B0.52s

Llama 3.1 Nemotron Safety Guard 8B v30.18s

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

GPT OSS Safeguard 120B6.08s

Llama 3.1 Nemotron Safety Guard 8B v32.96s

Simulador Interactivo de Costos de Tokens

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)

GPT OSS Safeguard 120B Monthly API Bill

$0.79 / month

$0.15/1M in · $0.6/1M out

Llama 3.1 Nemotron Safety Guard 8B v3 Monthly API Bill

$0.18 / month

$0.05/1M in · $0.1/1M out

Llama 3.1 Nemotron Safety Guard 8B v3 saves approximately $0.61 / month (77%) under this workload.4.4x Savings

GPT OSS Safeguard 120B · Strengths & Key Advantages

Ventana de contexto de 131K con hasta 33K tokens de salida máxima (SWE-bench Verified 41% · GPQA Diamond 65%)
Rendimiento ágil de 90 tokens/segundo con latencia inicial (TTFT) de solo 520 ms
Pesos abiertos (117B (5.1B MoE)) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama

Considerations & Trade-offs

Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Llama 3.1 Nemotron Safety Guard 8B v3 · Strengths & Key Advantages

Ventana de contexto de 128K con hasta 2K tokens de salida máxima (Arena Elo 1160)
Rendimiento ágil de 180 tokens/segundo con latencia inicial (TTFT) de solo 180 ms
Pesos abiertos (8B) listos para autoalojamiento local o en nube privada mediante vLLM y Ollama

Considerations & Trade-offs

Requiere infraestructura GPU dedicada con suficiente memoria VRAM para inferencia local sin cuantización
En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Token Use & Task Economics

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

Metric	GPT OSS Safeguard 120B	Llama 3.1 Nemotron Safety Guard 8B v3
Cost per Task Estimated USD to finish one task	$0.13	$0.01
Output Tokens / Task Tokens generated per task	40K	2K
Reasoning Tokens / Task Thinking tokens burned per task	20K	0K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	GPT OSS Safeguard 120B	Llama 3.1 Nemotron Safety Guard 8B v3
Official API Model ID (SDK)	gpt-oss-safeguard-120b	llama-3-1-nemotron-safety-guard-8b-v3
API Protocol	OpenAI Responses API & Chat Completions v1	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-10	2025-10
Knowledge Cutoff	June 2024	August 2025
Architecture	Sparse MoE safety-classifier model	Specialized Guardrail Classifier Transformer
Parameters	117B (5.1B active MoE)	8B
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 ($0.15/1M in) across full 131K window	Flat rate ($0.05/1M in) across full 128K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.015/1M (no extra cache-write fee)	Cached input at $0.01/1M tokens
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	Text-only completion (No GUI action loop)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Prompt-based JSON extraction only
Web Search Grounding & Sandbox	Native Web Search tool + Hosted Code Interpreter & File Search RAG	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) · 73 GB VRAM (4-bit Quantized) · 252 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16)
Safety & Frontier Classification	OpenAI Preparedness Framework Audited & System Card Published	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

GPT OSS Safeguard 120B vs Llama 3.1 Nemotron Safety Guard 8B v3: Respuestas Rápidas (FAQ)

Which is more intelligent, GPT OSS Safeguard 120B or Llama 3.1 Nemotron Safety Guard 8B v3?

GPT OSS Safeguard 120B is more intelligent. It scores 52 compared with 36 on the composite Intelligence Index.

Which model is faster?

Llama 3.1 Nemotron Safety Guard 8B v3 is faster, generating 180 tokens per second compared with 90 tokens per second.

Which model is cheaper to run?

Llama 3.1 Nemotron Safety Guard 8B v3 is cheaper at $0.03 per 1M tokens blended, compared with $0.10 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Llama 3.1 Nemotron Safety Guard 8B v3 has lower latency, with a time to first token of 0.18s compared with 0.52s.

Which model has a larger context window?

GPT OSS Safeguard 120B has a larger context window, supporting 131.1K tokens compared with 128K tokens.

Veredicto

Tanto GPT OSS Safeguard 120B (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) como Llama 3.1 Nemotron Safety Guard 8B v3 (Ideal para autoalojamiento en servidores propios, ajuste fino (fine-tuning) y soberanía de datos, sistemas RAG empresariales y automatización mediante API.) destacan en producción: GPT OSS Safeguard 120B lidera en inteligencia general y programación, Llama 3.1 Nemotron Safety Guard 8B v3 ofrece mayor velocidad de generación de tokens y Llama 3.1 Nemotron Safety Guard 8B v3 resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, GPT OSS Safeguard 120B o Llama 3.1 Nemotron Safety Guard 8B v3?+

En las pruebas de inteligencia compuesta y resolución de código, GPT OSS Safeguard 120B obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de GPT OSS Safeguard 120B frente a Llama 3.1 Nemotron Safety Guard 8B v3?+

GPT OSS Safeguard 120B cuesta $0.15 / $0.60 por millón de tokens de entrada/salida, mientras que Llama 3.1 Nemotron Safety Guard 8B v3 cuesta $0.05 / $0.10. En costo combinado, Llama 3.1 Nemotron Safety Guard 8B v3 es la opción más económica.

¿Qué modelo tiene mayor ventana de contexto y menor latencia?+

GPT OSS Safeguard 120B cuenta con 131.1K tokens de contexto frente a 128K tokens de Llama 3.1 Nemotron Safety Guard 8B v3. En velocidad de inferencia, Llama 3.1 Nemotron Safety Guard 8B v3 ofrece un rendimiento superior.

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)

GPT OSS Safeguard 120B vs Llama 3.1 Nemotron Safety Guard 8B v3

Cambia y Compara Cualquier Modelo

GPT OSS Safeguard 120B

Llama 3.1 Nemotron Safety Guard 8B v3

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

GPT OSS Safeguard 120B · Strengths & Key Advantages

Considerations & Trade-offs

Llama 3.1 Nemotron Safety Guard 8B v3 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

GPT OSS Safeguard 120B vs Llama 3.1 Nemotron Safety Guard 8B v3: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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