[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 parameters, it was trained on a…
Model details →Microsoft: Phi 4 vs ReMM SLERP 13B
Microsoft: Phi 4 wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
A recreation trial of the original MythoMax-L2-B13 but with updated models. #merge
Model details →Side-by-side comparison
| Capability | Microsoft: Phi 4 | ReMM SLERP 13B | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 16K | 6K | 🏆 Microsoft: Phi 4 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.07 | $0.45 | 🏆 Microsoft: Phi 4 |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.14 | $0.65 | 🏆 Microsoft: Phi 4 |
| 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 ReMM SLERP 13B?
Microsoft: Phi 4 wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Microsoft: Phi 4 and ReMM SLERP 13B?
Input: $0.07 vs $0.45 per 1M tokens. Output: $0.14 vs $0.65 per 1M tokens.
What context windows do Microsoft: Phi 4 and ReMM SLERP 13B support?
Microsoft: Phi 4 supports up to 16K tokens. ReMM SLERP 13B supports up to 6K tokens.
Do both Microsoft: Phi 4 and ReMM SLERP 13B support tool calling?
Microsoft: Phi 4: not advertised. ReMM SLERP 13B: not advertised.