MacBook Air M4 24GBBudget pick
C86.4 tok/s decode
~$1,099 MSRP
Can it run?
Runs well
Using Q4_K_M in Ollama
Fit status
Runs well
Decode
414.7 tok/s
TTFT
467 ms
Safe context
60K
Memory
4.3 GB / 16.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Runs well | 339.8 tok/s | 829 ms | 120K |
| Chat | C | Runs well | 339.8 tok/s | 350 ms | 30K |
| Coding | C | Runs well | 414.7 tok/s | 467 ms | 60K |
| RAG | C | Runs well | 339.8 tok/s | 1036 ms | 120K |
| Reasoning | C | Runs well | 339.8 tok/s | 673 ms | 60K |
How TinyLlama 1.1B Chat v1.0 (1.100000023841858B params) fits at each quantization level on Radeon RX 7900M 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.4 GB | Low | D30 |
Q3_K_S | 3 | 0.5 GB | Low | D30 |
NVFP4 | 4 |
Upgrade options
~$1,099 MSRP
~$1,999 MSRP
0.6 GB |
| Medium |
| D30 |
Q4_K_M | 4 | 0.7 GB | Medium | D30 |
Q5_K_M | 5 | 0.8 GB | High | D30 |
Q6_K | 6 | 0.9 GB | High | D31 |
Q8_0 | 8 | 1.2 GB | Very High | D31 |
F16Best for your GPU | 16 | 2.3 GB | Maximum | D32 |