Llama 3.1 Nemotron Safety Guard 8B v3 vs GPT-6 Astra
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Llama 3.1 Nemotron Safety Guard 8B v3 by NVIDIA against GPT-6 Astra by OpenAI across real-world coding, reasoning, token economics, and latency.
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Llama 3.1 Nemotron Safety Guard 8B v3
Modello Base a Pesi ApertiLlama 3.1 Nemotron Safety Guard 8B v3 di NVIDIA è un modello di IA progettato per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, con finestra di contesto da 128K, velocità di 180 token/s, indice di
$0.05 / 1M
$0.10 / 1M
128K tokens
N/A
GPT-6 Astra
Modello Vocale e Audio NativoGPT-6 Astra di OpenAI è un modello di IA progettato per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, con finestra di contesto da 272K, velocità di 100 token/s, indice di intelligenza di 96/100 e tariffa
$10.00 / 1M
$50.00 / 1M
272K tokens
82.4%
Differenze Chiave a Colpo d’Occhio
- Llama 3.1 Nemotron Safety Guard 8B v3 is 341.7x cheaper for API usage (input + output tokens combined).
- GPT-6 Astra has a larger context window (272K vs 128K tokens).
- Llama 3.1 Nemotron Safety Guard 8B v3 is faster at 180 tok/s vs 100 tok/s.
| Feature | Llama 3.1 Nemotron Safety Guard 8B v3 | GPT-6 Astra |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 36 | 96 |
Provider | NVIDIA | OpenAI |
Input Price Cost per million input tokens | $0.05 / 1M | $10.00 / 1M |
Output Price Cost per million output tokens | $0.10 / 1M | $50.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.03 / 1M | $7.70 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 272K tokens~408 A4 pages of text |
Max Output Tokens Per single request | 2K | 128K |
Throughput Speed Tokens generated per second | 180 tok/s | 100 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 82.4% |
GPQA Diamond Graduate-level reasoning | N/A | 80.9% |
Cached Input Price Prompt caching discount per 1M tokens | $0.01 / 1M | $1.00 / 1M |
Chi vince in ogni categoria?
At-a-glance decision frameworkEvaluations ongoing
Punteggi Benchmark Verificati
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.
Latenza e Tempo di Risposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulatore Interattivo dei Costi Token
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Llama 3.1 Nemotron Safety Guard 8B v3 · Strengths & Key Advantages
- Finestra di contesto da 128K con capacità massima di output fino a 2K token (Arena Elo 1160)
- Throughput elevato di 180 token/secondo con latenza al primo token (TTFT) di soli 180 ms
- Pesi aperti (8B) pronti per il self-hosting locale o su cloud privato tramite vLLM, SGLang o Ollama
Considerations & Trade-offs
- Richiede server GPU dedicati con sufficiente memoria VRAM per l’esecuzione locale a piena precisione
- Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità
GPT-6 Astra · Strengths & Key Advantages
- Finestra di contesto da 272K con capacità massima di output fino a 128K token (SWE-bench Verified 82.4% · GPQA Diamond 80.9%)
- Throughput elevato di 100 token/secondo con latenza al primo token (TTFT) di soli 950 ms
- Economia API competitiva ($10/$50 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
- Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
- Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Llama 3.1 Nemotron Safety Guard 8B v3 | GPT-6 Astra |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.01 | $2.15 |
Output Tokens / Task Tokens generated per task | 2K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 32K |
Specifiche Tecniche
Architecture, release timeline, capabilities, and modalities.
| Feature | Llama 3.1 Nemotron Safety Guard 8B v3 | GPT-6 Astra |
|---|---|---|
| Official API Model ID (SDK) | llama-3-1-nemotron-safety-guard-8b-v3 | gpt-6-astra |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-10 | 2026-09 |
| Knowledge Cutoff | August 2025 | June 2026 |
| Architecture | Specialized Guardrail Classifier Transformer | Omni-Adaptive Autoregressive with Dynamic CoT |
| Parameters | 8B | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.05/1M in) across full 128K window | Flat rate ($10/1M in) across full 272K window |
| Prompt Cache Policy & TTL | Cached input at $0.01/1M tokens | Automatic prefix caching at $1/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Text-only completion (No GUI action loop) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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) | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 5 GB VRAM (4-bit Quantized) · 17 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| 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 | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision, audio |
| Output Modalities | text | text, audio |
Llama 3.1 Nemotron Safety Guard 8B v3 vs GPT-6 Astra: Risposte Rapide (FAQ)
Which is more intelligent, Llama 3.1 Nemotron Safety Guard 8B v3 or GPT-6 Astra?
GPT-6 Astra is more intelligent. It scores 96 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 100 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 $7.70 (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 0.95s.
Which model has a larger context window?
GPT-6 Astra has a larger context window, supporting 272K tokens compared with 128K tokens.
Verdetto
Choose Llama 3.1 Nemotron Safety Guard 8B v3 for ideale per il self-hosting su infrastruttura privata, il fine-tuning e la piena sovranità dei dati, sistemi rag aziendali e integrazioni api scalabili., or choose GPT-6 Astra for ideale per la sintesi vocale naturale, l’elaborazione audio in tempo reale e la trascrizione, sistemi rag aziendali e integrazioni api scalabili..
Domande Frequenti (FAQ)
Which is cheaper: Llama 3.1 Nemotron Safety Guard 8B v3 or GPT-6 Astra?+
Llama 3.1 Nemotron Safety Guard 8B v3 costs $0.05/1M input and $0.1/1M output tokens, while GPT-6 Astra costs $10/1M input and $50/1M output tokens.
Which model has a larger context window: Llama 3.1 Nemotron Safety Guard 8B v3 or GPT-6 Astra?+
Llama 3.1 Nemotron Safety Guard 8B v3 supports 128K tokens whereas GPT-6 Astra supports 272K tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
Fonti ufficiali: NVIDIA & OpenAI Official Documentation