Llama Guard 3 1B vs Phi-4 Mini Reasoning
Llama Guard 3 1B (2024) and Phi-4 Mini Reasoning (2026) are frontier reasoning models from AI at Meta and Microsoft Research. Llama Guard 3 1B ships a 128k-token context window, while Phi-4 Mini Reasoning ships a 128k-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.
Phi-4 Mini Reasoning is safer overall; choose Llama Guard 3 1B when provider fit matters.
Decision scorecard
Local evidence first| Signal | Llama Guard 3 1B | Phi-4 Mini Reasoning |
|---|---|---|
| Best for | general production evaluation | reasoning-heavy apps |
| Decision fit | Long context and Classification | Long context |
| Context window | 128k | 128k |
| Cheapest output | $0.10/1M tokens | - |
| Provider routes | 1 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama Guard 3 1B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama Guard 3 1B for Long context and Classification.
- Phi-4 Mini Reasoning uniquely exposes Reasoning in local model data.
- Local decision data tags Phi-4 Mini Reasoning for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama Guard 3 1B
$105
Cheapest tracked route/tier: Fireworks AI
Phi-4 Mini Reasoning
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 Llama Guard 3 1B and Phi-4 Mini Reasoning; plan for SDK, billing, or endpoint changes.
- Phi-4 Mini Reasoning adds Reasoning in local capability data.
- No overlapping tracked provider route is sourced for Phi-4 Mini Reasoning and Llama Guard 3 1B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-09-25 | 2026-05-16 |
| Context window | 128k | 128k |
| Parameters | 1B | 3.8B |
| Architecture | decoder only | - |
| License | Llama 2 Community | MIT(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2023-12 | 2025-02 |
Pricing and availability
| Pricing attribute | Llama Guard 3 1B | Phi-4 Mini Reasoning |
|---|---|---|
| Input price | $0.10/1M tokens | - |
| Output price | $0.10/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Llama Guard 3 1B | Phi-4 Mini Reasoning |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | Yes |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: Phi-4 Mini Reasoning. 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: Llama Guard 3 1B has $0.10/1M input tokens and Phi-4 Mini Reasoning has no token price sourced yet. Provider availability is 1 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama Guard 3 1B when provider fit and broader provider choice are central to the workload. Choose Phi-4 Mini Reasoning when reasoning depth 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Llama Guard 3 1B or Phi-4 Mini Reasoning?
Llama Guard 3 1B supports 128k tokens, while Phi-4 Mini Reasoning supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama Guard 3 1B or Phi-4 Mini Reasoning open source?
Llama Guard 3 1B is listed under Llama 2 Community. Phi-4 Mini Reasoning is listed under MIT. 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 reasoning mode, Llama Guard 3 1B or Phi-4 Mini Reasoning?
Phi-4 Mini Reasoning 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.
Where can I run Llama Guard 3 1B and Phi-4 Mini Reasoning?
Llama Guard 3 1B is available on Fireworks AI. Phi-4 Mini Reasoning is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama Guard 3 1B over Phi-4 Mini Reasoning?
Phi-4 Mini Reasoning is safer overall; choose Llama Guard 3 1B when provider fit matters. If your workload also depends on provider fit, start with Llama Guard 3 1B; if it depends on reasoning depth, run the same evaluation with Phi-4 Mini Reasoning.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.