Nemotron Content Safety Reasoning 4B vs GPT OSS Safeguard 120B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Nemotron Content Safety Reasoning 4B da NVIDIA e GPT OSS Safeguard 120B da OpenAI são dois modelos de IA de destaque. O Nemotron Content Safety Reasoning 4B oferece uma janela de contexto de 128K tokens a $0.05/$0.15 por milhão de tokens, enquanto o GPT OSS Safeguard 120B oferece 131.1K tokens de contexto a $0.15/$0.60 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Nemotron Content Safety Reasoning 4B
Raciocínio de Pesos AbertosO Nemotron Content Safety Reasoning 4B da NVIDIA é um modelo de IA projetado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, oferecendo janela de contexto de 128K, velocidade de 150 tokens/s, índice de inteligên
$0.05 / 1M
$0.15 / 1M
128K tokens
N/A
GPT OSS Safeguard 120B
Modelo Base de Pesos AbertosO GPT OSS Safeguard 120B da OpenAI é um modelo de IA projetado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, oferecendo janela de contexto de 131K, velocidade de 90 tokens/s, índice de inteligência de 52/
$0.15 / 1M
$0.60 / 1M
131.1K tokens
41%
Principais Diferenças em Resumo
- Nemotron Content Safety Reasoning 4B is 3.5x cheaper for API usage (input + output tokens combined).
- GPT OSS Safeguard 120B has a larger context window (131K vs 128K tokens).
- Nemotron Content Safety Reasoning 4B is faster at 150 tok/s vs 90 tok/s.
| Feature | Nemotron Content Safety Reasoning 4B | GPT OSS Safeguard 120B |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 38 | 52 |
Provider | NVIDIA | OpenAI |
Input Price Cost per million input tokens | $0.05 / 1M | $0.15 / 1M |
Output Price Cost per million output tokens | $0.15 / 1M | $0.60 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.03 / 1M | $0.10 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 131.1K tokens~197 A4 pages of text |
Max Output Tokens Per single request | 4K | 33K |
Throughput Speed Tokens generated per second | 150 tok/s | 90 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 41% |
GPQA Diamond Graduate-level reasoning | N/A | 65% |
Cached Input Price Prompt caching discount per 1M tokens | $0.01 / 1M | $0.01 / 1M |
Quem vence em cada categoria?
At-a-glance decision frameworkEvaluations ongoing
Pontuações de Benchmarks Verificadas
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.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
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.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Nemotron Content Safety Reasoning 4B · Strengths & Key Advantages
- Janela de contexto de 128K com limite máximo de saída de 4K tokens (Arena Elo 1190)
- Taxa de transferência rápida de 150 tokens/segundo com latência inicial (TTFT) de 240 ms
- Pesos abertos (4B) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama
Considerations & Trade-offs
- Requer servidores GPU com memória VRAM adequada para execução local em precisão total
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
GPT OSS Safeguard 120B · Strengths & Key Advantages
- Janela de contexto de 131K com limite máximo de saída de 33K tokens (SWE-bench Verified 41% · GPQA Diamond 65%)
- Taxa de transferência rápida de 90 tokens/segundo com latência inicial (TTFT) de 520 ms
- Pesos abertos (117B (5.1B MoE)) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama
Considerations & Trade-offs
- Requer servidores GPU com memória VRAM adequada para execução local em precisão total
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Nemotron Content Safety Reasoning 4B | GPT OSS Safeguard 120B |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.02 | $0.13 |
Output Tokens / Task Tokens generated per task | 4K | 40K |
Reasoning Tokens / Task Thinking tokens burned per task | 2K | 20K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Nemotron Content Safety Reasoning 4B | GPT OSS Safeguard 120B |
|---|---|---|
| Official API Model ID (SDK) | nemotron-content-safety-reasoning-4b | gpt-oss-safeguard-120b |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-01 | 2025-10 |
| Knowledge Cutoff | November 2025 | June 2024 |
| Architecture | Reasoning-Augmented Safety Classifier | Sparse MoE safety-classifier model |
| Parameters | 4B | 117B (5.1B 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 ($0.05/1M in) across full 128K window | Flat rate ($0.15/1M in) across full 131K window |
| Prompt Cache Policy & TTL | Cached input at $0.01/1M tokens | Automatic prefix caching at $0.015/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Text-only completion (No GUI action loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Prompt-based JSON extraction only | 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| 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) · 2 GB VRAM (4-bit Quantized) · 9 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 73 GB VRAM (4-bit Quantized) · 252 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | OpenAI Preparedness Framework Audited & System Card Published |
| 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 Content Safety Reasoning 4B vs GPT OSS Safeguard 120B: Respostas Rápidas (FAQ)
Which is more intelligent, Nemotron Content Safety Reasoning 4B or GPT OSS Safeguard 120B?
GPT OSS Safeguard 120B is more intelligent. It scores 52 compared with 38 on the composite Intelligence Index.
Which model is faster?
Nemotron Content Safety Reasoning 4B is faster, generating 150 tokens per second compared with 90 tokens per second.
Which model is cheaper to run?
Nemotron Content Safety Reasoning 4B 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?
Nemotron Content Safety Reasoning 4B has lower latency, with a time to first token of 0.24s 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.
Veredito
Tanto Nemotron Content Safety Reasoning 4B (Indicado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, arquiteturas RAG corporativas e integração escalável via API.) quanto GPT OSS Safeguard 120B (Indicado para auto-hospedagem em infraestrutura própria, fine-tuning e soberania de dados, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: GPT OSS Safeguard 120B lidera em inteligência geral e programação, Nemotron Content Safety Reasoning 4B oferece geração mais rápida e Nemotron Content Safety Reasoning 4B apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, Nemotron Content Safety Reasoning 4B ou GPT OSS Safeguard 120B?+
Nas avaliações de inteligência e código, GPT OSS Safeguard 120B leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, Nemotron Content Safety Reasoning 4B ou GPT OSS Safeguard 120B?+
O Nemotron Content Safety Reasoning 4B custa $0.05 / $0.15 por 1M de tokens (entrada/saída) e o GPT OSS Safeguard 120B custa $0.15 / $0.60. No custo combinado, Nemotron Content Safety Reasoning 4B é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O Nemotron Content Safety Reasoning 4B suporta 128K tokens de contexto contra 131.1K tokens do GPT OSS Safeguard 120B, enquanto Nemotron Content Safety Reasoning 4B entrega maior velocidade de geração.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- GPT OSS Safeguard 120B vs. Llama 3.1 Nemotron Safety Guard 8B v3: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Nemotron 3.5 Content Safety vs. GPT OSS Safeguard 120B: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Nemotron 3 Content Safety vs. GPT OSS Safeguard 120B: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Nemotron 3 Content Safety vs. Nemotron Content Safety Reasoning 4B: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Nemotron Content Safety Reasoning 4B vs. Llama 3.1 Nemotron Safety Guard 8B v3: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
- Aion-3.0 vs. Aion-Mini: Comparação de Benchmarks, Preços API e Velocidade (2026)Comparar
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.
Fontes oficiais: Documentação oficial de API da NVIDIA e OpenAI e benchmarks independentes (2026).