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text model · Falcon · macOS

Can I run Falcon-H1-34B-Instruct on Apple M5 (16GB)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. Falcon-H1-34B-Instruct needs ~21.1 GB even at Q4_K_M, but Apple M5 (16GB) only has ~10.5 GB usable.

Needs ~21.1 GB Device usable ~10.5 GB

Needs ~21.1 GB even at Q4_K_M, but only ~10.5 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 10.6 GB: Falcon-H1-34B-Instruct needs roughly 21.1 GB at Q4_K_M and Apple M5 (16GB) leaves only about 10.5 GB usable for a model. The lightest tracked hardware that runs Falcon-H1-34B-Instruct is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Falcon-H1-34B-Instruct on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed
~21.1 GB
Usable on device
~10.5 GB
Device memory
16 GB
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Which quant fits

Quant ladder vs ~10.5 GB usable
Q2_K
~16.4 GB
Q3_K_M
~18.8 GB
Q4_K_M
~21.1 GB
Q5_K_M
~26.4 GB
Q6_K
~30.1 GB
Q8_0
~35.5 GB
FP16
~69.5 GB
The line marks Apple M5 (16GB)'s ~10.5 GB budget; rungs past it are too large.

How to run it

On macOS use LM Studio (Polished GUI, ships MLX on Apple Silicon, one-click model downloads.).

Model Falcon
Parameters
34B
Q4_K_M size
18.94 GB
Q8_0 size
33.31 GB
Context
256k
Full Falcon-H1-34B-Instruct requirements →
Device macOS
Memory
16 GB unified
Usable for weights
~10.5 GB
Best runtime
MLX direct / Ollama (MLX backend)
Best models for Apple M5 (16GB) →

What you can run instead

Run Falcon-H1-34B-Instruct on other hardware

FAQ

Can Apple M5 (16GB) run Falcon-H1-34B-Instruct?

No. Falcon-H1-34B-Instruct needs ~21.1 GB even at Q4_K_M, but Apple M5 (16GB) only has ~10.5 GB usable.

How much memory does Falcon-H1-34B-Instruct need?

Apple M5 (16GB) does not have enough memory. At Q4_K_M the weights are ~18.94 GB; with KV cache and runtime overhead, budget ~21.1 GB at a 4k context.

What is the best tool to run Falcon-H1-34B-Instruct on macOS?

LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.

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Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.