Llama 3.1 405B vs Phi 3.5 Mini Instruct
Llama 3.1 405B (2024) and Phi 3.5 Mini Instruct (2024) are compact production models from AI at Meta and Microsoft Research. Llama 3.1 405B ships a 128K-token context window, while Phi 3.5 Mini Instruct ships a 128K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Phi 3.5 Mini Instruct is safer overall; choose Llama 3.1 405B when provider fit matters.
Decision scorecard
Local evidence first| Signal | Llama 3.1 405B | Phi 3.5 Mini Instruct |
|---|---|---|
| Decision fit | Coding, Long context, and Classification | Long context |
| Context window | 128K | 128K |
| Cheapest output | - | $0.9/1M tokens |
| Provider routes | 0 tracked | 2 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Llama 3.1 405B for Coding, Long context, and Classification.
- Phi 3.5 Mini Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Phi 3.5 Mini Instruct for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 3.1 405B
Unavailable
No complete token price in local provider data
Phi 3.5 Mini Instruct
$945
Cheapest tracked route: Fireworks AI
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Llama 3.1 405B and Phi 3.5 Mini Instruct; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for Phi 3.5 Mini Instruct and Llama 3.1 405B; plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 2024-08-20 |
| Context window | 128K | 128K |
| Parameters | 405B | 3.8B |
| Architecture | decoder only | decoder only |
| License | Open Source | MIT |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Llama 3.1 405B | Phi 3.5 Mini Instruct |
|---|---|---|
| Input price | - | $0.9/1M tokens |
| Output price | - | $0.9/1M tokens |
| Providers | - |
Capabilities
| Capability | Llama 3.1 405B | Phi 3.5 Mini Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
Pricing coverage is uneven: Llama 3.1 405B has no token price sourced yet and Phi 3.5 Mini Instruct has $0.9/1M input tokens. Provider availability is 0 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3.1 405B when provider fit are central to the workload. Choose Phi 3.5 Mini Instruct when provider fit 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. 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 3.1 405B or Phi 3.5 Mini Instruct?
Llama 3.1 405B supports 128K tokens, while Phi 3.5 Mini Instruct 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 3.1 405B or Phi 3.5 Mini Instruct open source?
Llama 3.1 405B is listed under Open Source. Phi 3.5 Mini Instruct 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.
Where can I run Llama 3.1 405B and Phi 3.5 Mini Instruct?
Llama 3.1 405B is available on the tracked providers still being sourced. Phi 3.5 Mini Instruct is available on Fireworks AI and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3.1 405B over Phi 3.5 Mini Instruct?
Phi 3.5 Mini Instruct is safer overall; choose Llama 3.1 405B when provider fit matters. If your workload also depends on provider fit, start with Llama 3.1 405B; if it depends on provider fit, run the same evaluation with Phi 3.5 Mini Instruct.
Continue comparing
Last reviewed: 2026-05-01. Data sourced from public model cards and provider documentation.