Raises estimated decode speed by about 176%.
Adds memory headroom for longer context windows and future model growth.
~$12,000 MSRP
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VOOZH | about |
Falcon 40B Instruct needs ~41.4 GB VRAM. RTX PRO 6000 Blackwell Server Edition 96GB has 96.0 GB. With Q5_K_M quantization, expect ~52 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
51.7 tok/s
TTFT
3747 ms
Safe context
8K
Memory
41.4 GB / 96.0 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 | B | Runs well | 51.7 tok/s | 2044 ms | 8K |
| Coding | B | Runs well | 51.7 tok/s | 3747 ms | 8K |
| Agentic Coding | A | Runs well | 51.7 tok/s | 5450 ms | 8K |
| Reasoning | B | Runs well | 51.7 tok/s | 4428 ms | 8K |
| RAG | A | Runs well | 51.7 tok/s | 6813 ms | 8K |
How Falcon 40B Instruct (40B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | B61 |
Q3_K_S | 3 | 19.6 GB | Low | B61 |
NVFP4 | 4 | 22.4 GB | Medium | B62 |
Q4_K_M | 4 | 24.4 GB | Medium | B62 |
Q5_K_M | 5 | 28.8 GB | High | B63 |
Q6_K | 6 | 32.8 GB | High | B64 |
Q8_0 | 8 | 42.8 GB | Very High | B66 |
F16Best for your GPU | 16 | 82.0 GB | Maximum | B68 |
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 99Upgrade options
Raises estimated decode speed by about 176%.
Adds memory headroom for longer context windows and future model growth.
~$12,000 MSRP
Raises estimated decode speed by about 86%.
Adds memory headroom for longer context windows and future model growth.
~$15,000 MSRP