Falcon 40B Instruct needs ~44.6 GB VRAM. AMD Instinct MI250 128GB has 128.0 GB. With Q5_K_M quantization, expect ~84 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
83.8 tok/s
TTFT
2310 ms
Safe context
8K
Memory
44.6 GB / 128.0 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 | 83.8 tok/s | 1260 ms | 8K |
| Coding | B | Runs well | 83.8 tok/s | 2310 ms | 8K |
| Agentic Coding | A | Runs well | 83.8 tok/s | 3360 ms | 8K |
| Reasoning | B | Runs well | 83.8 tok/s | 2730 ms | 8K |
| RAG | A | Runs well | 83.8 tok/s | 4200 ms | 8K |
Inference speed
Estimated decode speed (tokens/sec) for Falcon 40B Instruct at Q5_K_M across popular GPUs and Apple Silicon, including multi-GPU rigs, using the fastest local runtime per device. Fastest is 2× RX 7900 XTX 24GB at ~45 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
2× RX 7900 XTX 24GB | 48 GB | Q5_K_M | 45.3 | Fits |
| 48 GB | Q5_K_M | 41.3 | Fits | |
| 48 GB | Q5_K_M | 35.3 | Fits | |
| 48 GB | Q5_K_M | 31.1 | Fits | |
| 32 GB | Q5_K_M | 29.4 | Heavy offload | |
MacBook Pro M4 Max 128GB | 128 GB | Q5_K_M | 23.1 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q5_K_M | 23.1 | Tight |
Mac Studio M3 Ultra 256GB | 256 GB | Q5_K_M | 21.5 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q5_K_M | 17.9 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q5_K_M | 16.9 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q5_K_M | 12.9 | Offloads |
| 24 GB | Q5_K_M | 10.5 | Too big | |
RX 7900 XTX 24GB | 24 GB | Q5_K_M | 9.5 | Too big |
MacBook Pro M3 Max 64GB | 64 GB | Q5_K_M | 9.2 | Tight |
| 24 GB | Q5_K_M | 9.0 | Too big | |
MacBook Pro M1 Max 64GB | 64 GB | Q5_K_M | 8.5 | Tight |
| 16 GB | Q5_K_M | 3.7 | Too big | |
| 12 GB | Q5_K_M | 2.2 | Too big | |
| 12 GB | Q5_K_M | 2.0 | Too big | |
| 8 GB | Q5_K_M | 2.0 | Too big |
Estimates for single-stream decoding at Q5_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How Falcon 40B Instruct (40B params) fits at each quantization level on AMD Instinct MI250 128GB (128.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | B59 |
Q3_K_S | 3 | 19.6 GB | Low | B60 |
NVFP4 | 4 | 22.4 GB | Medium | B60 |
Q4_K_M | 4 | 24.4 GB | Medium | B60 |
Q5_K_M | 5 | 28.8 GB | High | B61 |
Q6_K | 6 | 32.8 GB | High | B62 |
Q8_0 | 8 | 42.8 GB | Very High | B63 |
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 99Yes, AMD Instinct MI250 128GB can run Falcon 40B Instruct with a B grade (Runs well). Expected decode speed: 83.8 tok/s.
Falcon 40B Instruct (40B parameters) requires approximately 44.6 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 AMD Instinct MI250 128GB, Falcon 40B Instruct achieves approximately 83.8 tokens per second decode speed with a time-to-first-token of 2310ms using Q5_K_M quantization.
For coding workloads, Falcon 40B Instruct on AMD Instinct MI250 128GB receives a B grade with 83.8 tok/s and 8K context.
On AMD Instinct MI250 128GB, 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-instinct-mi250-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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