Falcon 7B Instruct needs ~15.7 GB VRAM. MacBook Pro M2 Max 96GB has 69.1 GB. With Q4_K_M quantization, expect ~60 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
59.7 tok/s
TTFT
3243 ms
Safe context
8K
Memory
15.7 GB / 69.1 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 | 59.7 tok/s | 1769 ms | 8K |
| Coding | B | Runs well | 59.7 tok/s | 3243 ms | 8K |
| Agentic Coding | B | Runs well | 59.7 tok/s | 4718 ms | 8K |
| Reasoning | B | Runs well | 59.7 tok/s | 3833 ms | 8K |
| RAG | B | Runs well | 59.7 tok/s | 5897 ms | 8K |
How Falcon 7B Instruct (7B params) fits at each quantization level on MacBook Pro M2 Max 96GB (69.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B56 |
Q3_K_S | 3 | 3.4 GB | Low | B56 |
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 64%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 64%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 62%.
Adds memory headroom for longer context windows and future model growth.
~$4,999 MSRP
Yes, MacBook Pro M2 Max 96GB can run Falcon 7B Instruct with a B grade (Runs well). Expected decode speed: 59.7 tok/s.
Falcon 7B Instruct (7B parameters) requires approximately 15.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Falcon 7B Instruct is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M2 Max 96GB, Falcon 7B Instruct achieves approximately 59.7 tokens per second decode speed with a time-to-first-token of 3243ms using Q4_K_M quantization.
For coding workloads, Falcon 7B Instruct on MacBook Pro M2 Max 96GB receives a B grade with 59.7 tok/s and 8K context.
On MacBook Pro M2 Max 96GB, Falcon 7B Instruct can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/falcon-7b-instruct-on-m2-max-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
3.9 GB |
| Medium |
| B56 |
Q4_K_M | 4 | 4.3 GB | Medium | B56 |
Q5_K_M | 5 | 5.0 GB | High | B56 |
Q6_K | 6 | 5.7 GB | High | B56 |
Q8_0 | 8 | 7.5 GB | Very High | B57 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | B58 |
Not always. MacBook Pro M2 Max 96GB 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.