GPT-5.4 vs Llama Guard 4 12B
GPT-5.4 (2026) and Llama Guard 4 12B (2025) are frontier reasoning models from OpenAI and AI at Meta. GPT-5.4 ships a not-yet-sourced context window, while Llama Guard 4 12B ships a 164K-token context window. On pricing, Llama Guard 4 12B costs $0.18/1M input tokens versus $2.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama Guard 4 12B is ~1289% cheaper at $0.18/1M; pay for GPT-5.4 only for coding workflow support.
Specs
| Released | 2026-03-05 | 2025-04-05 |
| Context window | — | 164K |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| GPT-5.4 | Llama Guard 4 12B | |
|---|---|---|
| Input price | $2.5/1M tokens | $0.18/1M tokens |
| Output price | $15/1M tokens | $0.18/1M tokens |
| Providers |
Capabilities
| GPT-5.4 | Llama Guard 4 12B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: GPT-5.4, reasoning mode: GPT-5.4, function calling: GPT-5.4, tool use: GPT-5.4, and code execution: GPT-5.4. Both models share structured outputs, 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.
For cost, GPT-5.4 lists $2.5/1M input and $15/1M output tokens, while Llama Guard 4 12B lists $0.18/1M input and $0.18/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama Guard 4 12B lower by about $6.07 per million blended tokens. Availability is 2 providers versus 3, so concentration risk also matters.
Choose GPT-5.4 when coding workflow support are central to the workload. Choose Llama Guard 4 12B when provider fit, lower input-token cost, and broader provider choice 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. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which is cheaper, GPT-5.4 or Llama Guard 4 12B?
Llama Guard 4 12B is cheaper on tracked token pricing. GPT-5.4 costs $2.5/1M input and $15/1M output tokens. Llama Guard 4 12B costs $0.18/1M input and $0.18/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.4 or Llama Guard 4 12B open source?
GPT-5.4 is listed under Proprietary. Llama Guard 4 12B is listed under Open Source. 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 multimodal input, GPT-5.4 or Llama Guard 4 12B?
GPT-5.4 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 reasoning mode, GPT-5.4 or Llama Guard 4 12B?
GPT-5.4 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, GPT-5.4 or Llama Guard 4 12B?
GPT-5.4 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.4 and Llama Guard 4 12B?
GPT-5.4 is available on OpenAI API and OpenRouter. Llama Guard 4 12B is available on NVIDIA NIM, Replicate API, and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.