Falcon 40B Instruct needs ~35.8 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q5_K_M quantization, expect ~50 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
Tight fit
Decode
50.3 tok/s
TTFT
3848 ms
Safe context
8K
Memory
35.8 GB / 40.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Tight fit | 50.3 tok/s | 2099 ms | 8K |
| Coding | A | Tight fit | 50.3 tok/s | 3848 ms | 8K |
| Agentic Coding | A | Tight fit | 50.3 tok/s | 5597 ms | 8K |
| Reasoning | A | Tight fit | 50.3 tok/s | 4548 ms | 8K |
| RAG | A | Tight fit | 50.3 tok/s | 6997 ms | 8K |
How Falcon 40B Instruct (40B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | B67 |
Q3_K_S | 3 | 19.6 GB | Low | B69 |
NVFP4 | 4 | 22.4 GB | Medium | B69 |
Q4_K_M | 4 | 24.4 GB | Medium | B69 |
Q5_K_MBest for your GPU | 5 | 28.8 GB | High | B69 |
Q6_K | 6 | 32.8 GB | High | F0 |
Q8_0 | 8 | 42.8 GB | Very High | F0 |
F16 | 16 | 82.0 GB | Maximum | F0 |
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 |
|---|---|---|---|---|
 Kimi Linear 48B A3B | 48B | A | 44.6 tok/s |
Yes, NVIDIA A100 40GB can run Falcon 40B Instruct with a A grade (Tight fit). Expected decode speed: 50.3 tok/s.
Falcon 40B Instruct (40B parameters) requires approximately 35.8 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 NVIDIA A100 40GB, Falcon 40B Instruct achieves approximately 50.3 tokens per second decode speed with a time-to-first-token of 3848ms using Q5_K_M quantization.
For coding workloads, Falcon 40B Instruct on NVIDIA A100 40GB receives a A grade with 50.3 tok/s and 8K context.
On NVIDIA A100 40GB, 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-a100-40gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: