Falcon 40B Instruct needs ~42.2 GB VRAM. Mac Studio M3 Ultra 96GB has 69.1 GB. With Q5_K_M quantization, expect ~22 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
21.5 tok/s
TTFT
9026 ms
Safe context
8K
Memory
42.2 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 | A | Runs well | 21.5 tok/s | 4923 ms | 8K |
| Coding | A | Runs well | 21.5 tok/s | 9026 ms | 8K |
| Agentic Coding | A | Runs well | 21.5 tok/s | 13128 ms | 8K |
| Reasoning | A | Runs well | 21.5 tok/s | 10667 ms | 8K |
| RAG | A | Runs well | 21.5 tok/s | 16410 ms | 8K |
How Falcon 40B Instruct (40B params) fits at each quantization level on Mac Studio M3 Ultra 96GB (69.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | B63 |
Q3_K_S | 3 | 19.6 GB | Low | B64 |
NVFP4 | 4 |
Copy-paste commands to run Falcon 40B Instruct on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "tiiuae/falcon-40b-instruct" \
--hf-file "falcon-40b-instruct-Q5_K_M.gguf" \
-c 4096 -ngl 99Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 2.5 VL 72B | 72B | S | 13.8 tok/s | |
| Qwen3-Coder-Next | 80B | S | 37.6 tok/s |
Yes, Mac Studio M3 Ultra 96GB can run Falcon 40B Instruct with a A grade (Runs well). Expected decode speed: 21.5 tok/s.
Falcon 40B Instruct (40B parameters) requires approximately 42.2 GB of memory with Q5_K_M quantization.
The recommended quantization for Falcon 40B Instruct is Q5_K_M, which balances quality and memory efficiency.
On Mac Studio M3 Ultra 96GB, Falcon 40B Instruct achieves approximately 21.5 tokens per second decode speed with a time-to-first-token of 9026ms using Q5_K_M quantization.
For coding workloads, Falcon 40B Instruct on Mac Studio M3 Ultra 96GB receives a A grade with 21.5 tok/s and 8K context.
On Mac Studio M3 Ultra 96GB, Falcon 40B 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-40b-instruct-on-m3-ultra-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
22.4 GB |
| Medium |
| B64 |
Q4_K_M | 4 | 24.4 GB | Medium | B65 |
Q5_K_M | 5 | 28.8 GB | High | B66 |
Q6_K | 6 | 32.8 GB | High | B67 |
Q8_0Best for your GPU | 8 | 42.8 GB | Very High | B68 |
F16 | 16 | 82.0 GB | Maximum | F0 |
 Llama 3.3 70B | 70B | A | 14.2 tok/s |
 Kimi Linear 48B A3B | 48B | A | 19 tok/s |
| Llama 3.1 70B | 70B | A | 14.2 tok/s |
Not always. Mac Studio M3 Ultra 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.