Raises estimated decode speed by about 117%.
~$2,499 MSRP
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VOOZH | about |
Falcon 7B Instruct needs ~8.7 GB VRAM. MacBook Pro M1 Pro 32GB has 23.0 GB. With Q4_K_M quantization, expect ~30 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
33.4 tok/s
TTFT
5788 ms
Safe context
8K
Memory
8.7 GB / 23.0 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 33.4 tok/s | 3157 ms | 8K |
| Coding | B | Runs well | 30.4 tok/s | 6359 ms | 8K |
| Agentic Coding | B | Runs well | 33.4 tok/s | 8419 ms | 8K |
| Reasoning | B | Runs well | 33.4 tok/s | 6841 ms | 8K |
| RAG | B | Runs well | 33.4 tok/s | 10524 ms | 8K |
How Falcon 7B Instruct (7B params) fits at each quantization level on MacBook Pro M1 Pro 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B61 |
Q3_K_S | 3 | 3.4 GB | Low | B61 |
NVFP4 | 4 |
Copy-paste commands to run Falcon 7B Instruct on your machine.
Run
lms load falcon-7b-instruct && lms server startUpgrade options
Raises estimated decode speed by about 117%.
~$2,499 MSRP
Raises estimated decode speed by about 189%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Raises estimated decode speed by about 85%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
3.9 GB |
| Medium |
| B61 |
Q4_K_M | 4 | 4.3 GB | Medium | B61 |
Q5_K_M | 5 | 5.0 GB | High | B62 |
Q6_K | 6 | 5.7 GB | High | B62 |
Q8_0 | 8 | 7.5 GB | Very High | B63 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | B66 |
Not always. MacBook Pro M1 Pro 32GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.