GPT-4 Turbo vs Llama 3.1 NemoGuard 8B Content Safety
GPT-4 Turbo (2024) and Llama 3.1 NemoGuard 8B Content Safety (2025) are compact production models from OpenAI and NVIDIA AI. GPT-4 Turbo ships a 128K-token context window, while Llama 3.1 NemoGuard 8B Content Safety ships a 4K-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-4 Turbo fits 32x more tokens; pick it for long-context work and Llama 3.1 NemoGuard 8B Content Safety for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-4 Turbo | Llama 3.1 NemoGuard 8B Content Safety |
|---|---|---|
| Best for | multimodal apps, tool-calling agents, and provider-routed production | general production evaluation |
| Decision fit | Coding, RAG, and Agents | Classification |
| Context window | 128K | 4K |
| Cheapest output | $15/1M tokens | - |
| Provider routes | 6 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- GPT-4 Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-4 Turbo has broader tracked provider coverage for fallback and route flexibility.
- GPT-4 Turbo uniquely exposes Vision, Multimodal, and JSON / Tool use in local model data.
- Local decision data tags GPT-4 Turbo for Coding, RAG, and Agents.
- Local decision data tags Llama 3.1 NemoGuard 8B Content Safety for Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-4 Turbo
$7,750
Cheapest tracked route/tier: Replicate API
Llama 3.1 NemoGuard 8B Content Safety
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GPT-4 Turbo and Llama 3.1 NemoGuard 8B Content Safety; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Multimodal, and JSON / Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 3.1 NemoGuard 8B Content Safety and GPT-4 Turbo; plan for SDK, billing, or endpoint changes.
- GPT-4 Turbo adds Vision, Multimodal, and JSON / Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-09 | 2025-01-01 |
| Context window | 128K | 4K |
| Parameters | 1.76T (8x222B MoE)* | 8B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Proprietary | NVIDIA Open Model |
| Openness | Proprietary | Open weights |
| Weights | Not released | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Restricted | Permitted |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | GPT-4 Turbo | Llama 3.1 NemoGuard 8B Content Safety |
|---|---|---|
| Input price | $5/1M tokens | - |
| Output price | $15/1M tokens | - |
| Providers |
Capabilities
| Capability | GPT-4 Turbo | Llama 3.1 NemoGuard 8B Content Safety |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| JSON / Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on vision: GPT-4 Turbo, multimodal input: GPT-4 Turbo, JSON / Tool use: GPT-4 Turbo, JSON / Tool use: GPT-4 Turbo, structured outputs: GPT-4 Turbo, and code execution: GPT-4 Turbo. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: GPT-4 Turbo has $5/1M input tokens and Llama 3.1 NemoGuard 8B Content Safety has no token price sourced yet. Provider availability is 6 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GPT-4 Turbo when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Llama 3.1 NemoGuard 8B Content Safety when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, GPT-4 Turbo or Llama 3.1 NemoGuard 8B Content Safety?
GPT-4 Turbo supports 128K tokens, while Llama 3.1 NemoGuard 8B Content Safety supports 4K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is GPT-4 Turbo or Llama 3.1 NemoGuard 8B Content Safety open source?
GPT-4 Turbo is listed under Proprietary. Llama 3.1 NemoGuard 8B Content Safety is listed under NVIDIA Open Model. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-4 Turbo or Llama 3.1 NemoGuard 8B Content Safety?
GPT-4 Turbo has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-4 Turbo or Llama 3.1 NemoGuard 8B Content Safety?
GPT-4 Turbo has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for JSON / Tool use, GPT-4 Turbo or Llama 3.1 NemoGuard 8B Content Safety?
GPT-4 Turbo has the clearer documented JSON / Tool use signal in this comparison. If JSON / Tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-4 Turbo and Llama 3.1 NemoGuard 8B Content Safety?
GPT-4 Turbo is available on OpenAI API, Azure OpenAI, Salesforce Models API, OpenRouter, and Replicate API. Llama 3.1 NemoGuard 8B Content Safety is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-10-17. Data sourced from public model cards and provider documentation.