Yes — Inkling-Small (276B) runs at 45 tok/s on M5 Ultra with 256 GB RAM using Q4_K_M quantization via MLX. First token latency is Nones. A capable open-source LLM with 276B parameters.
Want to run Inkling-Small faster — or step up to bigger models? Find your Mac →The LLMCheck index estimates Inkling-Small on M5 Ultra using our published methodology: Q4_K_M quantization, memory-bandwidth scaling, and cross-referenced third-party benchmarks where available. Figures are transparent estimates — own this config? Submit a real benchmark →
| Metric | Value |
|---|---|
| Tokens per second | 45 tok/s |
| Time to first token | Nones |
| Quantization | Q4_K_M |
| Minimum RAM | 256 GB |
| Recommended engine | MLX |
| Parameters | 276B |
| Benchmark date | 2026-08 |
Q4_K_M 276B MLX M5 Ultra
The recommended engine for Inkling-Small on M5 Ultra is MLX. Install with pip and pull the model:
Alternatively, you can use Ollama for a simpler setup:
| Chip | Speed | First Token | Min RAM | Engine |
|---|---|---|---|---|
| M3 Ultra | 18 tok/s | 0.9s | 512 GB | MLX |
To run Inkling-Small on M5 Ultra you need:
Inkling-Small needs about 256 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Inkling-Small stacks up against other models on your specific Mac hardware.
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