Canonical Rankings

Best Macs for this model

Mistral Small 3.1 24B ranked across the Mac lineup at the best practical quantization, using the best available runtime evidence. Historical baseline selected; model picker is focused on current-market choices.

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29 ranked MacsUse the strongest current runtime evidence for each row.27 other historical models hiddenBaselinesStatic paths cover only canonical model pages; sort and quantization stay as query state.

Historical baseline selected: Mistral Small 3.1 24B. Default model choices remain current-market; other historical models stay hidden.

Rank	Mac	Score	Quant	Tok/s	Runtime	Fits	Headroom	Context	Evidence	Price	Why it ranks here
1	Mac Studio M3 Ultra 256GB	282	8bit	Measure it	llama.cpp	Fits	231.9 GB	131k	Fit-first	$7,499	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 231.9 GB headroom remains at this quantization.
2	Mac Pro M2 Ultra 192GB	218	8bit	Measure it	llama.cpp	Fits	167.9 GB	131k	Fit-first	$6,999	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 167.9 GB headroom remains at this quantization.
3	Mac Studio M4 Max 128GB	154	8bit	Measure it	llama.cpp	Fits	103.9 GB	131k	Fit-first	$4,499	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 103.9 GB headroom remains at this quantization.
4	MacBook Pro M5 Max 128GB 16-inch	154	8bit	Measure it	llama.cpp	Fits	103.9 GB	131k	Fit-first	$5,399	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 103.9 GB headroom remains at this quantization.
5	MacBook Pro M4 Max 128GB 16-inch	154	8bit	Measure it	llama.cpp	Fits	103.9 GB	131k	Fit-first	$5,999	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 103.9 GB headroom remains at this quantization.
6	Mac Studio M3 Ultra 96GB	122	8bit	Measure it	llama.cpp	Fits	71.9 GB	131k	Fit-first	$3,999	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 71.9 GB headroom remains at this quantization.
7	Mac Studio M4 Max 64GB	90	8bit	Measure it	llama.cpp	Fits	39.9 GB	131k	Fit-first	$2,999	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 39.9 GB headroom remains at this quantization.
8	MacBook Pro M4 Max 64GB 16-inch	90	8bit	Measure it	llama.cpp	Fits	39.9 GB	131k	Fit-first	$4,499	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 39.9 GB headroom remains at this quantization.
9	Mac Mini M4 Pro 48GB	74	8bit	Measure it	llama.cpp	Fits	23.9 GB	118k	Fit-first	$1,599	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 23.9 GB headroom remains at this quantization.
10	MacBook Pro M4 Pro 48GB 14-inch	74	8bit	Measure it	llama.cpp	Fits	23.9 GB	118k	Fit-first	$2,499	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 23.9 GB headroom remains at this quantization.
11	Mac Studio M4 Max 48GB	74	8bit	Measure it	llama.cpp	Fits	23.9 GB	118k	Fit-first	$2,499	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 23.9 GB headroom remains at this quantization.
12	MacBook Pro M4 Pro 48GB 16-inch	74	8bit	Measure it	llama.cpp	Fits	23.9 GB	118k	Fit-first	$2,999	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 23.9 GB headroom remains at this quantization.
13	MacBook Pro M4 Max 48GB 14-inch	74	8bit	Measure it	llama.cpp	Fits	23.9 GB	118k	Fit-first	$3,499	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 23.9 GB headroom remains at this quantization.
14	MacBook Pro M4 Max 48GB 16-inch	74	8bit	Measure it	llama.cpp	Fits	23.9 GB	118k	Fit-first	$3,999	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 23.9 GB headroom remains at this quantization.
15	Mac Studio M4 Max 36GB	62	8bit	Measure it	llama.cpp	Fits	11.9 GB	51k	Fit-first	$1,999	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 11.9 GB headroom remains at this quantization.
16	MacBook Pro M4 Max 36GB 14-inch	62	8bit	Measure it	llama.cpp	Fits	11.9 GB	51k	Fit-first	$2,999	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 11.9 GB headroom remains at this quantization.
17	MacBook Pro M4 Max 36GB 16-inch	62	8bit	Measure it	llama.cpp	Fits	11.9 GB	51k	Fit-first	$3,499	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 11.9 GB headroom remains at this quantization.
18	Mac Mini M4 32GB	58	8bit	Measure it	llama.cpp	Fits	7.9 GB	28k	Fit-first	$799	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 7.9 GB headroom remains at this quantization.
19	MacBook Air M4 32GB 13-inch	58	8bit	Measure it	llama.cpp	Fits	7.9 GB	28k	Fit-first	$1,499	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 7.9 GB headroom remains at this quantization.
20	MacBook Air M4 32GB 15-inch	58	8bit	Measure it	llama.cpp	Fits	7.9 GB	28k	Fit-first	$1,699	8bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 7.9 GB headroom remains at this quantization.
21	Mac Mini M4 24GB	48	Q6_K	Measure it	llama.cpp	Fits	3.9 GB	10k	Fit-first	$599	Q6_K is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 3.9 GB headroom remains at this quantization.
22	MacBook Air M4 24GB 13-inch	48	Q6_K	Measure it	llama.cpp	Fits	3.9 GB	10k	Fit-first	$1,299	Q6_K is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 3.9 GB headroom remains at this quantization.
23	Mac Mini M4 Pro 24GB	48	Q6_K	Measure it	llama.cpp	Fits	3.9 GB	10k	Fit-first	$1,399	Q6_K is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 3.9 GB headroom remains at this quantization.
24	MacBook Air M4 24GB 15-inch	48	Q6_K	Measure it	llama.cpp	Fits	3.9 GB	10k	Fit-first	$1,499	Q6_K is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 3.9 GB headroom remains at this quantization.
25	MacBook Pro M4 Pro 24GB 14-inch	48	Q6_K	Measure it	llama.cpp	Fits	3.9 GB	10k	Fit-first	$1,999	Q6_K is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 3.9 GB headroom remains at this quantization.
26	MacBook Pro M4 Pro 24GB 16-inch	48	Q6_K	Measure it	llama.cpp	Fits	3.9 GB	10k	Fit-first	$2,499	Q6_K is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 3.9 GB headroom remains at this quantization.
27	Mac Mini M4 16GB	41	q4.1bit	Measure it	llama.cpp	Fits	2.8 GB	11k	Fit-first	$499	q4.1bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 2.8 GB headroom remains at this quantization.
28	MacBook Air M4 16GB 13-inch	41	q4.1bit	Measure it	llama.cpp	Fits	2.8 GB	11k	Fit-first	$1,099	q4.1bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 2.8 GB headroom remains at this quantization.
29	MacBook Air M4 16GB 15-inch	41	q4.1bit	Measure it	llama.cpp	Fits	2.8 GB	11k	Fit-first	$1,299	q4.1bit is the current best practical quantization. This Mac fits, but speed still needs direct speed coverage. 2.8 GB headroom remains at this quantization.

Mistral Small 3.1 24B — ranking first, catalog record below

Start with the ranked Mac table above. Use the rest of this page to inspect raw Apple Silicon coverage and model metadata.

0Benchmark rows

0Chip tiers covered

—Fastest avg tok/s

—Minimum RAM observed

Quick take

Mistral Small 3.1 24B is cataloged because Apple Silicon buyers are already searching for it. Mistral Small 3.1 24B: 3 practitioner claims; 3 captured from fetched artifacts; hardware mentions: 24GB, 32GB, M1 Pro, M4; runtime mentions: llama.cpp, Ollama; themes: apple_silicon_viability, coding_quality, fit_and_memory, model_comparison, operational_caution, runtime_tuning; includes operational caveats. Use the ranking above for the current best Mac path, then open Bench when direct evidence lands.

3 practitioner signals tracked so far, no benchmarks yet.

Need the best Mac for this model? Use Buy Need a setup-first answer? Use Run Checking whether it fits? Use Fit Browse Macs by exact hardware Need the full audit trail? Use Bench Comparing against rented GPUs? Use AI Datacenter Index

Catalog record

24BTotal params

DenseActive params

131,072Context window

2025-03-11Release date

This is a reference-only model record. It remains useful for historical benchmarks, migration checks, and audit context, but it is excluded from current frontier packs.

No Apple Silicon benchmark rows are published for this model yet.

What this model is, and what Apple Silicon users are actually seeing

Official model cards tell you what the model is for and which software stacks it targets. Field reality below shows how much Apple Silicon evidence we have so far.

Official brief

Building upon Mistral Small 3 (2501), Mistral Small 3.1 (2503) adds state-of-the-art vision understanding and enhances long context capabilities up to 128k tokens without compromising text performance.

Official source · Raw model card

agentsreasoningvisual-understanding

Runtime support mentioned

vLLMTransformers

Official specs

Total parameters: 24B.
Context: 128k tokens.
Modalities: Text and image input, text output.
License: Apache 2.0.

Official takeaways

Note 1: We recommend using a relatively low temperature, such as temperature=0.15.
Building upon Mistral Small 3 (2501), Mistral Small 3.1 (2503) adds state-of-the-art vision understanding and enhances long context capabilities up to 128k tokens without compromising text performance.
Vision: Vision capabilities enable the model to analyze images and provide insights based on visual content in addition to text.
Mistral Small 3.1 can be deployed locally and is exceptionally "knowledge-dense," fitting within a single RTX 4090 or a 32GB RAM MacBook once quantized.

Deployment notes

Official model card says Mistral Small 3.1 can deploy locally and fit within a single RTX 4090 or a 32GB RAM MacBook once quantized.
Official model card recommends vLLM for production inference and notes Transformers-compatible weights are available but not thoroughly tested.

Apple Silicon note: Official model card says Mistral Small 3.1 can deploy locally and fit within a single RTX 4090 or a 32GB RAM MacBook once quantized.

Official model cards describe intent, capabilities, and supported stacks. They do not prove Apple Silicon speed by themselves.

Field reality on Apple Silicon

Mistral Small 3.1 24B: 1 Apple Silicon field report; best reported generation ~3.6 tok/s; reported RAM use ~13.5GB; seen on MacBook Air M5 32GB; via llama.cpp.

0Benchmark rows

1Field reports

3Practitioner signals

No BenchmarksEvidence status

What practitioners keep saying

The post reports a MacBook Air M5 32GB, 10 CPU/10 GPU setup using llama-bench with Q4_K_M quantization across 37 models.
In the reported slow-but-capable table, Mistral Small 3.1 24B reaches 3.6 tok/s generation and 13.5GB RAM use under Q4_K_M llama-bench on a MacBook Air M5 32GB.
The thread is centered on replacing parts of real agentic workflows with Mistral Small 3.1 rather than celebrating benchmark scores.

Apple Silicon field sources

r/LocalLLaMA
2026-04-06 · MacBook Air M5 32GB · llama.cpp
mac-llm-bench reports Mistral Small 3.1 as a slow-but-capable Q4_K_M GGUF row on a MacBook Air M5 32GB, grounding fit and speed while leaving first-party reproduction open.
r/LocalLLaMA
2025-06-15 · Local agentic workflow
Mistral Small 3.1 is getting serious practitioner adoption for structured output, tool use, and vision-heavy agentic workflows.
r/LocalLLaMA
2025-03-17 · Mac mini M4 24GB or M1 Pro 32GB · Ollama or chatllm.cpp
Mistral Small 3.1 is already being pushed onto modest Apple Silicon tiers, but its local behavior looks far more runtime-sensitive than benchmark-first marketing implies.

Runtime mentions in the field

llama.cppOllama

Hardware mentioned in reports

24GB32GBM1 ProM4MacMac MiniMacBook

What would improve confidence

Collect First Apple Silicon Benchmark
Reproduce Field Performance Signal
Upgrade To First Party Measurement

Current published coverage

This reference record stays published for audit and migration context, but Apple Silicon speed coverage is still missing.

Raw benchmark rows for Mistral Small 3.1 24B

Rows stay below the ranking because this page is answer-first. Use them to inspect exact chips, quantizations, runtimes, and sources.

No benchmark rows are published yet for this model. The ranking above still shows the best current Mac fit path, but the benchmark section stays empty until direct Apple Silicon measurements land.

Data

benchmarks.json — full dataset · models.json — model summaries · benchmarks.csv — CSV export

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