[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...
Model details →Microsoft: Phi 4 vs Sao10K: Llama 3 8B Lunaris
Sao10K: Llama 3 8B Lunaris wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
Lunaris 8B is a versatile generalist and roleplaying model based on Llama 3. It's a strategic merge of multiple models, designed to balance creativity with improved logic and general knowledge....
Model details →Side-by-side comparison
| Capability | Microsoft: Phi 4 | Sao10K: Llama 3 8B Lunaris | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 16K | 8K | 🏆 Microsoft: Phi 4 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.07 | $0.04 | 🏆 Sao10K: Llama 3 8B Lunaris |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.14 | $0.05 | 🏆 Sao10K: Llama 3 8B Lunaris |
| Tool / function calling First-class support for emitting structured tool calls. | — | — | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | — | Tie |
Frequently asked questions
Is Microsoft: Phi 4 better than Sao10K: Llama 3 8B Lunaris?
Sao10K: Llama 3 8B Lunaris wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Microsoft: Phi 4 and Sao10K: Llama 3 8B Lunaris?
Input: $0.07 vs $0.04 per 1M tokens. Output: $0.14 vs $0.05 per 1M tokens.
What context windows do Microsoft: Phi 4 and Sao10K: Llama 3 8B Lunaris support?
Microsoft: Phi 4 supports up to 16K tokens. Sao10K: Llama 3 8B Lunaris supports up to 8K tokens.
Do both Microsoft: Phi 4 and Sao10K: Llama 3 8B Lunaris support tool calling?
Microsoft: Phi 4: not advertised. Sao10K: Llama 3 8B Lunaris: not advertised.