Canonical Rankings

Best Macs for this model

Qwen3.5-27B ranked across the Mac lineup at the best practical quantization, using the best available runtime evidence. Model picker is focused on current-market choices.

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29 ranked MacsUse the strongest current runtime evidence for each row.28 historical models hiddenBaselinesStatic paths cover only canonical model pages; sort and quantization stay as query state.

Rank	Mac	Score	Quant	Tok/s	Runtime	Fits	Headroom	Context	Evidence	Price	Why it ranks here
1	Mac Studio M3 Ultra 256GB	446	8bit	38.0 tok/s Fastest evidence path: 8bit · 38.0 tok/s · MLX · Estimated	MLX	Fits	228.4 GB	262k	Estimated	$7,499	8bit is the current best practical quantization. 38.0 tok/s is estimated from nearby benchmark coverage. 228.4 GB headroom remains at this quantization.
2	Mac Pro M2 Ultra 192GB	295	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	164.4 GB	262k	Estimated	$6,999	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 164.4 GB headroom remains at this quantization.
3	MacBook Pro M5 Max 128GB 16-inch	293	8bit	31.6 tok/s Fastest evidence path: 8bit · 31.6 tok/s · MLX · Estimated	MLX	Fits	100.4 GB	262k	Estimated	$5,399	8bit is the current best practical quantization. 31.6 tok/s is estimated from nearby benchmark coverage. 100.4 GB headroom remains at this quantization.
4	Mac Studio M4 Max 128GB	231	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	100.4 GB	262k	Estimated	$4,499	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 100.4 GB headroom remains at this quantization.
5	MacBook Pro M4 Max 128GB 16-inch	231	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	100.4 GB	262k	Estimated	$5,999	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 100.4 GB headroom remains at this quantization.
6	Mac Studio M3 Ultra 96GB	199	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	68.4 GB	229k	Estimated	$3,999	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 68.4 GB headroom remains at this quantization.
7	Mac Studio M4 Max 64GB	167	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	36.4 GB	118k	Estimated	$2,999	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 36.4 GB headroom remains at this quantization.
8	MacBook Pro M4 Max 64GB 16-inch	167	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	36.4 GB	118k	Estimated	$4,499	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 36.4 GB headroom remains at this quantization.
9	Mac Studio M4 Max 48GB	151	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	20.4 GB	62k	Estimated	$2,499	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 20.4 GB headroom remains at this quantization.
10	MacBook Pro M4 Max 48GB 14-inch	151	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	20.4 GB	62k	Estimated	$3,499	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 20.4 GB headroom remains at this quantization.
11	MacBook Pro M4 Max 48GB 16-inch	151	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	20.4 GB	62k	Estimated	$3,999	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 20.4 GB headroom remains at this quantization.
12	Mac Studio M4 Max 36GB	139	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	8.4 GB	20k	Estimated	$1,999	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 8.4 GB headroom remains at this quantization.
13	MacBook Pro M4 Max 36GB 14-inch	139	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	8.4 GB	20k	Estimated	$2,999	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 8.4 GB headroom remains at this quantization.
14	MacBook Pro M4 Max 36GB 16-inch	139	8bit	16.1 tok/s Fastest evidence path: 8bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	8.4 GB	20k	Estimated	$3,499	8bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 8.4 GB headroom remains at this quantization.
15	Mac Mini M4 32GB	133	Q6_K	16.1 tok/s Fastest evidence path: Q6_K · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	8.9 GB	25k	Estimated	$799	Q6_K is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 8.9 GB headroom remains at this quantization.
16	MacBook Air M4 32GB 13-inch	133	Q6_K	16.1 tok/s Fastest evidence path: Q6_K · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	8.9 GB	25k	Estimated	$1,499	Q6_K is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 8.9 GB headroom remains at this quantization.
17	MacBook Air M4 32GB 15-inch	133	Q6_K	16.1 tok/s Fastest evidence path: Q6_K · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	8.9 GB	25k	Estimated	$1,699	Q6_K is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 8.9 GB headroom remains at this quantization.
18	Mac Mini M4 24GB	128	Q5_K_M	16.1 tok/s Fastest evidence path: Q5_K_M · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	3.6 GB	8k	Estimated	$599	Q5_K_M is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 3.6 GB headroom remains at this quantization.
19	MacBook Air M4 24GB 13-inch	128	Q5_K_M	16.1 tok/s Fastest evidence path: Q5_K_M · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	3.6 GB	8k	Estimated	$1,299	Q5_K_M is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 3.6 GB headroom remains at this quantization.
20	Mac Mini M4 Pro 24GB	128	Q5_K_M	16.1 tok/s Fastest evidence path: Q5_K_M · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	3.6 GB	8k	Estimated	$1,399	Q5_K_M is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 3.6 GB headroom remains at this quantization.
21	MacBook Air M4 24GB 15-inch	128	Q5_K_M	16.1 tok/s Fastest evidence path: Q5_K_M · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	3.6 GB	8k	Estimated	$1,499	Q5_K_M is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 3.6 GB headroom remains at this quantization.
22	MacBook Pro M4 Pro 24GB 14-inch	128	Q5_K_M	16.1 tok/s Fastest evidence path: Q5_K_M · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	3.6 GB	8k	Estimated	$1,999	Q5_K_M is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 3.6 GB headroom remains at this quantization.
23	MacBook Pro M4 Pro 24GB 16-inch	128	Q5_K_M	16.1 tok/s Fastest evidence path: Q5_K_M · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	3.6 GB	8k	Estimated	$2,499	Q5_K_M is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 3.6 GB headroom remains at this quantization.
24	Mac Mini M4 Pro 48GB	128	8bit	8.5 tok/s Fastest evidence path: 8bit · 8.5 tok/s · MLX · Community row	MLX	Fits	20.4 GB	62k	Community row	$1,599	8bit is the current best practical quantization. 8.5 tok/s is backed by direct benchmark coverage. 20.4 GB headroom remains at this quantization.
25	MacBook Pro M4 Pro 48GB 14-inch	128	8bit	8.5 tok/s Fastest evidence path: 8bit · 8.5 tok/s · MLX · Community row	MLX	Fits	20.4 GB	62k	Community row	$2,499	8bit is the current best practical quantization. 8.5 tok/s is backed by direct benchmark coverage. 20.4 GB headroom remains at this quantization.
26	MacBook Pro M4 Pro 48GB 16-inch	128	8bit	8.5 tok/s Fastest evidence path: 8bit · 8.5 tok/s · MLX · Community row	MLX	Fits	20.4 GB	62k	Community row	$2,999	8bit is the current best practical quantization. 8.5 tok/s is backed by direct benchmark coverage. 20.4 GB headroom remains at this quantization.
27	Mac Mini M4 16GB	93	3bit	16.1 tok/s Fastest evidence path: 3bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	4.1 GB	15k	Estimated	$499	3bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 4.1 GB headroom remains at this quantization.
28	MacBook Air M4 16GB 13-inch	93	3bit	16.1 tok/s Fastest evidence path: 3bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	4.1 GB	15k	Estimated	$1,099	3bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 4.1 GB headroom remains at this quantization.
29	MacBook Air M4 16GB 15-inch	93	3bit	16.1 tok/s Fastest evidence path: 3bit · 16.1 tok/s · llama.cpp · Estimated	llama.cpp	Fits	4.1 GB	15k	Estimated	$1,299	3bit is the current best practical quantization. 16.1 tok/s is estimated from nearby benchmark coverage. 4.1 GB headroom remains at this quantization.

Qwen3.5-27B — ranking first, raw rows below

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

Quantizations observed: 4bit, 8bit, Q4_K - Medium, Q4_K, Q6_K, Q8_0

18Benchmark rows

10Chip tiers covered

38.0Fastest avg tok/s (M3 Ultra (256 GB))

15.3 GBMinimum RAM observed

Quick take

Fastest published result is 38.0 tok/s on M3 Ultra (256 GB) at 4bit. Smallest published fit is 15.3 GB on M3 Ultra (256 GB). Longest published context on this page is 16k. Published runtimes include llama.cpp, MLX. Start with Rankings for the decision, then use the raw rows below to audit the evidence.

Based on 18 external benchmarks; no lab runs yet.

Published runtimes: llama.cpp, MLX.

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

27BTotal params

DenseActive params

262,144Context window

2026-02-24Release date

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

Unified Vision-Language Foundation: Early fusion training on multimodal tokens achieves cross-generational parity with Qwen3 and outperforms Qwen3-VL models across reasoning, coding, agents, and visual understanding benchmarks.

Official source · Raw model card

agentscodingreasoningvisual-understanding

Runtime support mentioned

vLLMSGLangTransformersKTransformers

Official specs

Type: Causal Language Model with Vision Encoder.
Scale: 27B.
Context: 262,144 natively and extensible up to 1,010,000 tokens.
Total parameters: 27B.
Max input: 262,144 natively and extensible up to 1,010,000 tokens.

Official takeaways

Unified Vision-Language Foundation: Early fusion training on multimodal tokens achieves cross-generational parity with Qwen3 and outperforms Qwen3-VL models across reasoning, coding, agents, and visual understanding ben…
Efficient Hybrid Architecture: Gated Delta Networks combined with sparse Mixture-of-Experts deliver high-throughput inference with minimal latency and cost overhead.
Scalable RL Generalization: Reinforcement learning scaled across million-agent environments with progressively complex task distributions for robust real-world adaptability.
Global Linguistic Coverage: Expanded support to 201 languages and dialects, enabling inclusive, worldwide deployment with nuanced cultural and regional understanding.

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

Field reality on Apple Silicon

Qwen3.5-27B: 20 Apple Silicon field reports; best reported generation ~32.8 tok/s; best reported prompt processing ~222.23 tok/s; seen on MacBook Pro M5 MAX 128GB, MacBook Pro M5 MAX 48GB, M2 ULTRA 128GB; via oMLX, MLX, llama.cpp.

18Benchmark rows

20Field reports

15Practitioner signals

Sparse BenchmarksEvidence status

What practitioners keep saying

The post reports Qwen3.5-27B dense on a MacBook Pro M3 Max 128GB at pp1024/tg128 with 23.0 tok/s generation under oMLX v0.2.23.
The post reports the same M3 Max 128GB Qwen3.5-27B dense run at 65000 tokens context with 6.8 tok/s generation.
The post reports Qwen3.5-27B dense on a MacBook Pro M5 Max 128GB at pp1024/tg128 with 32.8 tok/s generation under oMLX v0.2.23.

Apple Silicon field sources

r/LocalLLaMA
2026-03-28 · MacBook Pro M3 Max 128GB, MacBook Pro M5 Max 128GB · oMLX
The same oMLX comparison reports Qwen3.5-27B dense at 23.0 tg tok/s on a MacBook Pro M3 Max 128GB at pp1024/tg128.
r/LocalLLaMA
2026-03-26 · Mac Studio M1 Max 64GB, MacBook Pro M5 Max 48GB · llama.cpp, MLX
The benchmark bundle reports Qwen3.5-27B 4-bit MLX on a Mac Studio M1 Max 64GB at 15.0 tok/s generation in the 8K workload.
r/LocalLLaMA
2026-03-26 · Mac Mini M4 16GB · llama.cpp
A large 16GB M4 sweep says Qwen3.5-27B is a trap tier on constrained Apple Silicon: it may fit on paper, but it often collapses into memory-thrashing behavior.
SharpAI HomeSec-Bench
2026-03-26 · MacBook Pro M5 Pro 64GB · llama.cpp
The same M5 Pro 64GB Apple Silicon benchmark puts Qwen3.5-27B in the usable local-agent tier rather than the barely-fits category.
r/LocalLLaMA
2026-03-22 · MacBook Pro M1 Max 64GB · llama.cpp
Qwen3.5-27B remains usable on a 64GB M1 Max laptop, but the thread reinforces that older Apple Silicon tops out around the low-teens tok/s range in llama.cpp rather than feeling like a fast dense-model workstation.

6 more Apple Silicon field sources tracked in the research queue.

Runtime mentions in the field

llama.cppLM StudioMLXoMLX

Hardware mentioned in reports

16GB32GB48GB64GB96GB128GBM1 MaxM4

What would improve confidence

Reproduce Field Performance Signal
Upgrade To First Party Measurement

Current published coverage

Published chip coverage includes M3 Ultra (256 GB), M5 Max (128 GB), M5 Max (48 GB), M2 Ultra (GPU count not published, 128 GB), M4 Max plus 5 more chip tiers. Fastest published row is 38.0 tok/s on M3 Ultra (256 GB) at 4bit. Lowest published RAM requirement is 15.3 GB on M3 Ultra (256 GB). Catalog context window is 16k.

M3 Ultra (256 GB)M5 Max (128 GB)M5 Max (48 GB)M2 Ultra (GPU count not published, 128 GB)M4 Max M1 Max (64 GB)M2 Max (38-core GPU, 96 GB)M5 Pro (64 GB)

Related Qwen3.5-27B models with published pages: Qwen3.5-35B-A3B · Qwen3.5-9B · Qwen3.5-122B-A10B · Qwen3.5-397B-A17B · Qwen3.5-4B

Standardized eval scorecards for Qwen3.5-27B

These are fixed-machine model scorecards from a single Apple Silicon setup. They help explain whether a model is merely fast or actually good at tools, coding, reasoning, and general tasks. They do not replace the main Mac ranking above.

4bit · vLLM-MLX

Mac Studio M3 Ultra 256GB · Avg 76%

83%Tools

90%Coding

50%Reasoning

80%General

Speed and memory

Long decode: 37.7 tok/s
Short decode: 17.7 tok/s
Cold TTFT: 0.453 s
Active RAM: 15.3 GB

A strong fits-anywhere coding and tool-use compromise.

vLLM-MLX SCORECARD.md · discussion · 2026-03-04

Raw benchmark rows for Qwen3.5-27B

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

Chip	Quant	RAM req.	Context	Avg tok/s	Prompt tok/s	Runtime	Source
M3 Ultra (256 GB)	4bit	15.3 GB	—	38.0 tok/s	—	MLX	ref
M5 Max (128 GB)	4bit	—	—	31.6 tok/s	—	MLX	ref
M5 Max (48 GB)	4bit	—	8k	31.3 tok/s	779.0 tok/s	MLX	ref
M2 Ultra (GPU count not published, 128 GB)	8bit	—	—	27.1 tok/s	—	MLX	ref
M5 Max (48 GB)	Q4_K - Medium	—	8k	23.7 tok/s	171.0 tok/s	llama.cpp	ref
M2 Ultra (GPU count not published, 128 GB)	8bit	—	—	20.6 tok/s	—	MLX	ref
M4 Max	Q4_K	16.4 GB	2k	16.7 tok/s	222.2 tok/s	llama.cpp	ref
M5 Max (128 GB)	Q6_K	—	8k	16.5 tok/s	—	llama.cpp	ref
M4 Max	Q4_K	16.4 GB	8k	16.1 tok/s	209.3 tok/s	llama.cpp	ref
M4 Max	Q4_K	16.4 GB	16k	15.8 tok/s	195.4 tok/s	llama.cpp	ref
M1 Max (64 GB)	4bit	—	8k	15.0 tok/s	67.0 tok/s	MLX	ref
M1 Max (64 GB)	Q6_K	—	—	12.0 tok/s	—	llama.cpp	ref
M2 Max (38-core GPU, 96 GB)	8bit	30.0 GB	—	12.0 tok/s	—	MLX	ref
M1 Max (64 GB)	Q4_K - Medium	—	—	11.5 tok/s	—	llama.cpp	ref
M1 Max (64 GB)	Q8_0	—	—	10.5 tok/s	—	llama.cpp	ref
M5 Pro (64 GB)	Q4_K - Medium	24.9 GB	—	10.0 tok/s	—	llama.cpp	ref
M4 Pro (48 GB)	8bit	—	—	8.5 tok/s	—	MLX	ref
M4 (16 GB)	Q4_K - Medium	—	—	0.0 tok/s	—	llama.cpp	ref

Best Macs for Qwen3.5-27B

Ordered by fastest published tok/s on the chip family in each Mac. Click through for the full machine page.

Mac Studio M3 Ultra 96GB — 38.0 tok/s Mac Studio M3 Ultra 256GB — 38.0 tok/s MacBook Pro M5 Max 128GB 16-inch — 31.6 tok/s MacBook Pro M4 Max 36GB 14-inch — 16.7 tok/s MacBook Pro M4 Max 48GB 14-inch — 16.7 tok/s MacBook Pro M4 Max 36GB 16-inch — 16.7 tok/s

Chips with published results for Qwen3.5-27B

M3 Ultra (256 GB)M5 Max (128 GB)M5 Max (48 GB)M2 Ultra (GPU count not published, 128 GB)M4 Max M1 Max (64 GB)M2 Max (38-core GPU, 96 GB)M5 Pro (64 GB)M4 Pro (48 GB)M4 (16 GB)

Data

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

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