falcon mamba 7b instruct Q4 K M needs ~19.8 GB VRAM. MacBook Pro M3 Max 128GB has 92.2 GB. With Q4_K_M quantization, expect ~65 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
64.6 tok/s
TTFT
2995 ms
Safe context
1.4M
Memory
19.8 GB / 92.2 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 | C | Runs well | 64.6 tok/s | 1634 ms | 1.4M |
| Coding | C | Runs well | 64.6 tok/s | 2995 ms | 1.4M |
| Agentic Coding | C | Runs well | 64.6 tok/s | 4357 ms | 1.4M |
| Reasoning | C | Runs well | 64.6 tok/s | 3540 ms | 1.4M |
| RAG | C | Runs well | 64.6 tok/s | 5446 ms | 1.4M |
How falcon mamba 7b instruct Q4 K M (7B params) fits at each quantization level on MacBook Pro M3 Max 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | D39 |
Q3_K_S | 3 | 3.4 GB | Low | D39 |
NVFP4 | 4 |
Copy-paste commands to run falcon mamba 7b instruct Q4 K M on your machine.
Run
lms load hf-tiiuae--falcon-mamba-7b-instruct-q4-k-m-gguf && lms server startUpgrade options
Yes, MacBook Pro M3 Max 128GB can run falcon mamba 7b instruct Q4 K M with a C grade (Runs well). Expected decode speed: 64.6 tok/s.
falcon mamba 7b instruct Q4 K M (7B parameters) requires approximately 19.8 GB of memory with Q4_K_M quantization.
The recommended quantization for falcon mamba 7b instruct Q4 K M is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M3 Max 128GB, falcon mamba 7b instruct Q4 K M achieves approximately 64.6 tokens per second decode speed with a time-to-first-token of 2995ms using Q4_K_M quantization.
For coding workloads, falcon mamba 7b instruct Q4 K M on MacBook Pro M3 Max 128GB receives a C grade with 64.6 tok/s and 1.4M context.
On MacBook Pro M3 Max 128GB, falcon mamba 7b instruct Q4 K M can safely use up to 1.4M tokens of context. The model's official context limit is —, 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/hf-tiiuae--falcon-mamba-7b-instruct-q4-k-m-gguf-on-m3-max-128gb" 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 |
| D39 |
Q4_K_M | 4 | 4.3 GB | Medium | D39 |
Q5_K_M | 5 | 5.0 GB | High | D39 |
Q6_K | 6 | 5.7 GB | High | D39 |
Q8_0 | 8 | 7.5 GB | Very High | D39 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | D40 |
Not always. MacBook Pro M3 Max 128GB 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.