Ornith 1.5 9B on Apple M5 Max (64 GB)
Can the Apple M5 Max (64 GB) run Ornith 1.5 9B?
Yes, it runs well
Runs well. At Q6_K it needs about 12.6 GB of 48.0 GB usable, with an estimated speed of 46.7 tok/s.
- Best quant
Q6_K- Generation speed
- 46.7 tok/s
- Prompt processing
- 1,214 tok/s
- First token (1K prompt)
- 0.8 s
- Largest safe context
- 256K
Download Ornith 1.5 9B
Recommended for the Apple M5 Max (64 GB): Q6_K. Every other quantization has its own download link in the table below.
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q6_K file (opens in a new tab)
huggingface.co/ornith-ai/Ornith-1.5-9B-GGUF (opens in a new tab)
ollama run hf.co/ornith-ai/Ornith-1.5-9B-GGUF:Q6_KOriginal weights · Hugging Face
Full-precision files from DeepReinforce, for fine-tuning, vLLM, Transformers.
How the A grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 34.3 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 6.1 / 15 | |
| Total | 80.4 / 100 | 80 ptsGreat (A) · 80 of 100 points: Model quality 34.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.1/15 |
Every quantization on the Apple M5 Max (64 GB)
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 8.6 GB | 48.0 GB | 110 tok/s | Runs well | 68 ptsGood (B) · 68 of 100 points: Model quality 24.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.1/15 | GGUF files (opens in a new tab) |
Q3_K_M | 9.4 GB | 48.0 GB | 86.9 tok/s | Runs well | 73 ptsGreat (A) · 73 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.5/15 | GGUF files (opens in a new tab) |
Q4_K_M | 10.6 GB | 48.0 GB | 67.3 tok/s | Runs well | 78 ptsGreat (A) · 78 of 100 points: Model quality 32.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.1/15 | GGUF (opens in a new tab) |
Q5_K_M | 11.6 GB | 48.0 GB | 55.6 tok/s | Runs well | 79 ptsGreat (A) · 79 of 100 points: Model quality 33.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.6/15 | GGUF (opens in a new tab) |
Q6_K | 12.6 GB | 48.0 GB | 46.7 tok/s | Runs well | 80 ptsGreat (A) · 80 of 100 points: Model quality 34.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.1/15 | GGUF (opens in a new tab) |
Q8_0 | 14.9 GB | 48.0 GB | 34.2 tok/s | Runs well | 80 ptsGreat (A) · 80 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 13.9/15, Memory use 7.2/15 | GGUF (opens in a new tab) |
F16 | 24.0 GB | 48.0 GB | 15.8 tok/s | Runs well | 80 ptsGreat (A) · 80 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 9.4/15, Memory use 11.5/15 | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4070 Ti SUPER
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4080 SUPER
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5070 Ti
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5080
- 89 ptsExcellent (S) · 89 of 100 points: Model quality 34.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4070 SUPER
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.