Phi-4 reasoning 14B
Microsoft Phi-4 reasoning 14B, 4-bit GGUF on llama.cpp. Chat in your browser, plus an OpenAI-compatible API.
- Engine
- llama.cpp · Q4_K_M
- Size
- 9.1 GB
- GPU memory
- 11 GiB or more
- Runs on
Pick a machine
Picked Apple M4 Pro (20-core GPU): the lowest price that fits. No speed data for these GPUs yet.
Deploying accepts the rental terms. Unused budget comes back to your balance.
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Hardware that can run this
- M4 Pro · 24 GB unifiedDeployable now · $0.12/h
19 more devices could run it, none online
| Hardware | Fits | Est. speed |
|---|---|---|
| RTX 3080 Ti · 12 GB | Q4_K_M | 60–86 tok/s |
| M1 · 16 GB unified | Q4_K_M | Evidence unavailable: no cited memory bandwidth for this hardware |
| M1 Pro · 16 GB unified | Q4_K_M | 13–19 tok/s |
| M2 · 16 GB unified | Q4_K_M | 6–10 tok/s |
| M2 Pro · 16 GB unified | Q4_K_M | 13–19 tok/s |
| M3 · 16 GB unified | Q4_K_M | 6–10 tok/s |
| M4 · 16 GB unified | Q4_K_M | 7–12 tok/s |
| RX 6800 XT · 16 GB | Q4_K_M | Evidence unavailable: no cited memory bandwidth for this hardware |
| M3 Pro · 18 GB unified | Q4_K_M, Q8 | 9–15 tok/s |
| RTX 3090 · 24 GB | Q4_K_M, Q8 | 62–88 tok/s |
| RTX 4090 · 24 GB | Q4_K_M, Q8 | 66–95 tok/s |
| RX 7900 XTX · 24 GB | Q4_K_M, Q8 | Evidence unavailable: no cited memory bandwidth for this hardware |
| M1 Max · 32 GB unified | Q4_K_M, Q8 | 26–38 tok/s |
| M2 Max · 32 GB unified | Q4_K_M, Q8 | 26–38 tok/s |
| M3 Max · 48 GB unified | Q4_K_M, Q8, FP16 | 19–29 tok/s |
| M4 Max · 48 GB unified | Q4_K_M, Q8, FP16 | 27–39 tok/s |
| M4 Pro · 48 GB unified | Q4_K_M, Q8, FP16 | 18–26 tok/s |
| Instinct MI210 · 64 GB | Q4_K_M, Q8, FP16 | Evidence unavailable: no cited memory bandwidth for this hardware |
| M4 Max · 64 GB unified | Q4_K_M, Q8, FP16 | 27–39 tok/s |
Speeds are estimates from memory bandwidth and weight size, not measured benchmarks. A price is the cheapest listed offer for that hardware.
Template details
- Rating
- No ratings yet
- Runs
- 0
- Min VRAM
- 12 GB
- Backend
- Metal on Apple silicon
- Weights
- 9.1 GB
- Version
- llamacpp-phi-4-reasoning-v1.0.0
- Image digest
- 1f4b9cf58982…
- Health check
- SSH probe on the leased endpoint
We match GPUs on their measured runtime and dedicated VRAM. A hardware report doesn't qualify another vendor's backend.
#llm #chat #openai-api #gguf #reasoning
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