Gemma 4 31B runs at 31 tok/s on a 256 GB M5 Ultra, a community run reported by bohemiansilicon.com (MLX, QAT, 512-token random prompt, 128 generated, empty context, mean of 2). It needs about 24 GB of unified memory. It is Google's 31B dense model, released under the Apache 2.0 licence.
Want to run Gemma 4 31B faster — or step up to bigger models? Find your Mac →This is a community run: a real run, reported by its source and linked below. The index records it as given and never adjusts it.
| Metric | Value |
|---|---|
| Tokens per second | community31 tok/s |
| Provenance | community run · bohemiansilicon.com |
| Quantization | QAT |
| Engine | MLX |
| Context | 512-token random prompt, 128 generated, empty context, mean of 2 |
| Figure dated | 2026-10-15 |
| Minimum RAM | 24 GB |
| Parameters | 31B |
| Chip bandwidth | 1228 GB/s |
Each row as the index holds it, with its source. “Mac RAM” is the memory of the Mac a run used, not the model’s requirement (24 GB). The headline figure follows the reference rule: the lower-median measured plain-decode run at 5 bits or fewer (a run whose quant was not stated counts only when no stated-quant run qualifies), else the estimate; a run marked “not used to anchor estimates” is listed here but never becomes the headline.
| Speed | Quant | Engine | Mac RAM | Context | Source | Note |
|---|---|---|---|---|---|---|
| community31 tok/s | QAT | MLX | 256 GB | 512-token random prompt, 128 generated, empty context, mean of 2 | bohemiansilicon.com | Mac Studio, mlx-lm 0.32 on macOS 27.0.1, mlx-community QAT 4-bit build. 27 tok/s at 8K and 21 at 32K. Published by Bohemian Silicon, which rents out this Mac. |
Ollama — install it (brew install ollama or the app from ollama.com), then pull the model by its tag, checked on ollama.com on 2026-10-24:
MLX — pick a build from Hugging Face’s MLX listings, then run it with its repo id:
Downloads: Search the Ollama library → · model card →
The 31 tok/s figure above came from MLX at QAT; other runtimes and quants run at different speeds.
Prefer a GUI? LM Studio downloads GGUF and MLX builds in one click. Step by step: install Ollama on a Mac.
Google's dense 31B Gemma 4 with 256K context, Apache 2.0. Needs a 24 GB+ Mac at 4-bit; a community run measured ~8 tok/s on a 32 GB Mac mini M6 (QAT).
Apache 2.0 licence · 31B · 256K context · LLMCheck capability 40/50 · see its leaderboard rank →
Gemma 4 31B needs about 24 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Gemma 4 31B stacks up against other models on your specific Mac hardware.
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