Llama 3.1 Nemotron 70B Reward vs Phi-4 Mini Reasoning
Llama 3.1 Nemotron 70B Reward (2024) and Phi-4 Mini Reasoning (2026) are frontier reasoning models from NVIDIA AI and Microsoft Research. Llama 3.1 Nemotron 70B Reward ships a 4k-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 fits 32x more tokens; pick it for long-context work and Llama 3.1 Nemotron 70B Reward for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 3.1 Nemotron 70B Reward | Phi-4 Mini Reasoning |
|---|---|---|
| Best for | general production evaluation | reasoning-heavy apps |
| Decision fit | Classification | Long context |
| Context window | 4k | 128k |
| Cheapest output | - | - |
| Provider routes | 1 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama 3.1 Nemotron 70B Reward has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.1 Nemotron 70B Reward for Classification.
- Phi-4 Mini Reasoning has the larger context window for long prompts, retrieval packs, or transcript analysis.
- 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 3.1 Nemotron 70B Reward
Unavailable
No complete token price in local provider data
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 3.1 Nemotron 70B Reward 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 3.1 Nemotron 70B Reward; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-10-01 | 2026-05-16 |
| Context window | 4k | 128k |
| Parameters | 70B | 3.8B |
| Architecture | decoder only | - |
| License | 1 | Proprietary |
| Knowledge cutoff | - | 2025-02 |
Pricing and availability
| Pricing attribute | Llama 3.1 Nemotron 70B Reward | Phi-4 Mini Reasoning |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Llama 3.1 Nemotron 70B Reward | 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 3.1 Nemotron 70B Reward has no token price sourced yet 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 3.1 Nemotron 70B Reward when provider fit and broader provider choice are central to the workload. Choose Phi-4 Mini Reasoning when reasoning depth and larger context windows 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 Nemotron 70B Reward or Phi-4 Mini Reasoning?
Phi-4 Mini Reasoning supports 128k tokens, while Llama 3.1 Nemotron 70B Reward supports 4k 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 Nemotron 70B Reward or Phi-4 Mini Reasoning open source?
Llama 3.1 Nemotron 70B Reward is listed under 1. Phi-4 Mini Reasoning is listed under Proprietary. 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 3.1 Nemotron 70B Reward 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 3.1 Nemotron 70B Reward and Phi-4 Mini Reasoning?
Llama 3.1 Nemotron 70B Reward is available on NVIDIA NIM. 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 3.1 Nemotron 70B Reward over Phi-4 Mini Reasoning?
Phi-4 Mini Reasoning fits 32x more tokens; pick it for long-context work and Llama 3.1 Nemotron 70B Reward for tighter calls. If your workload also depends on provider fit, start with Llama 3.1 Nemotron 70B Reward; 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.