Canonical Rankings

Best Macs for this model

Qwen3.5-9B 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	736	8bit	106.0 tok/s Fastest evidence path: 8bit · 106.0 tok/s · MLX · Estimated	MLX	Fits	246.1 GB	262k	Estimated	$7,499	8bit is the current best practical quantization. 106.0 tok/s is estimated from nearby benchmark coverage. 246.1 GB headroom remains at this quantization.
2	MacBook Pro M5 Max 128GB 16-inch	496	8bit	78.0 tok/s Fastest evidence path: 8bit · 78.0 tok/s · MLX · Estimated	MLX	Fits	118.1 GB	262k	Estimated	$5,399	8bit is the current best practical quantization. 78.0 tok/s is estimated from nearby benchmark coverage. 118.1 GB headroom remains at this quantization.
3	Mac Mini M4 24GB	448	8bit	92.0 tok/s Fastest evidence path: 8bit · 92.0 tok/s · MLX · Estimated	MLX	Fits	14.1 GB	94k	Estimated	$599	8bit is the current best practical quantization. 92.0 tok/s is estimated from nearby benchmark coverage. 14.1 GB headroom remains at this quantization.
4	MacBook Air M4 24GB 13-inch	448	8bit	92.0 tok/s Fastest evidence path: 8bit · 92.0 tok/s · MLX · Estimated	MLX	Fits	14.1 GB	94k	Estimated	$1,299	8bit is the current best practical quantization. 92.0 tok/s is estimated from nearby benchmark coverage. 14.1 GB headroom remains at this quantization.
5	Mac Mini M4 Pro 24GB	448	8bit	92.0 tok/s Fastest evidence path: 8bit · 92.0 tok/s · MLX · Estimated	MLX	Fits	14.1 GB	94k	Estimated	$1,399	8bit is the current best practical quantization. 92.0 tok/s is estimated from nearby benchmark coverage. 14.1 GB headroom remains at this quantization.
6	MacBook Air M4 24GB 15-inch	448	8bit	92.0 tok/s Fastest evidence path: 8bit · 92.0 tok/s · MLX · Estimated	MLX	Fits	14.1 GB	94k	Estimated	$1,499	8bit is the current best practical quantization. 92.0 tok/s is estimated from nearby benchmark coverage. 14.1 GB headroom remains at this quantization.
7	MacBook Pro M4 Pro 24GB 14-inch	448	8bit	92.0 tok/s Fastest evidence path: 8bit · 92.0 tok/s · MLX · Estimated	MLX	Fits	14.1 GB	94k	Estimated	$1,999	8bit is the current best practical quantization. 92.0 tok/s is estimated from nearby benchmark coverage. 14.1 GB headroom remains at this quantization.
8	MacBook Pro M4 Pro 24GB 16-inch	448	8bit	92.0 tok/s Fastest evidence path: 8bit · 92.0 tok/s · MLX · Estimated	MLX	Fits	14.1 GB	94k	Estimated	$2,499	8bit is the current best practical quantization. 92.0 tok/s is estimated from nearby benchmark coverage. 14.1 GB headroom remains at this quantization.
9	Mac Pro M2 Ultra 192GB	388	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	182.1 GB	262k	Estimated	$6,999	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 182.1 GB headroom remains at this quantization.
10	Mac Studio M4 Max 128GB	324	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	118.1 GB	262k	Estimated	$4,499	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 118.1 GB headroom remains at this quantization.
11	MacBook Pro M4 Max 128GB 16-inch	324	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	118.1 GB	262k	Estimated	$5,999	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 118.1 GB headroom remains at this quantization.
12	Mac Studio M3 Ultra 96GB	292	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	86.1 GB	262k	Estimated	$3,999	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 86.1 GB headroom remains at this quantization.
13	Mac Studio M4 Max 64GB	260	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	54.1 GB	262k	Estimated	$2,999	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 54.1 GB headroom remains at this quantization.
14	MacBook Pro M4 Max 64GB 16-inch	260	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	54.1 GB	262k	Estimated	$4,499	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 54.1 GB headroom remains at this quantization.
15	Mac Mini M4 Pro 48GB	244	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	38.1 GB	261k	Estimated	$1,599	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 38.1 GB headroom remains at this quantization.
16	MacBook Pro M4 Pro 48GB 14-inch	244	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	38.1 GB	261k	Estimated	$2,499	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 38.1 GB headroom remains at this quantization.
17	Mac Studio M4 Max 48GB	244	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	38.1 GB	261k	Estimated	$2,499	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 38.1 GB headroom remains at this quantization.
18	MacBook Pro M4 Pro 48GB 16-inch	244	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	38.1 GB	261k	Estimated	$2,999	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 38.1 GB headroom remains at this quantization.
19	MacBook Pro M4 Max 48GB 14-inch	244	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	38.1 GB	261k	Estimated	$3,499	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 38.1 GB headroom remains at this quantization.
20	MacBook Pro M4 Max 48GB 16-inch	244	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	38.1 GB	261k	Estimated	$3,999	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 38.1 GB headroom remains at this quantization.
21	Mac Studio M4 Max 36GB	232	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	26.1 GB	178k	Estimated	$1,999	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 26.1 GB headroom remains at this quantization.
22	MacBook Pro M4 Max 36GB 14-inch	232	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	26.1 GB	178k	Estimated	$2,999	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 26.1 GB headroom remains at this quantization.
23	MacBook Pro M4 Max 36GB 16-inch	232	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	26.1 GB	178k	Estimated	$3,499	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 26.1 GB headroom remains at this quantization.
24	Mac Mini M4 32GB	228	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	22.1 GB	150k	Estimated	$799	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 22.1 GB headroom remains at this quantization.
25	MacBook Air M4 32GB 13-inch	228	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	22.1 GB	150k	Estimated	$1,499	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 22.1 GB headroom remains at this quantization.
26	MacBook Air M4 32GB 15-inch	228	8bit	35.0 tok/s Fastest evidence path: 8bit · 35.0 tok/s · llama.cpp · Estimated	llama.cpp	Fits	22.1 GB	150k	Estimated	$1,699	8bit is the current best practical quantization. 35.0 tok/s is estimated from nearby benchmark coverage. 22.1 GB headroom remains at this quantization.
27	Mac Mini M4 16GB	88	8bit	4.1 tok/s Fastest evidence path: Q4_K_M · 72.0 tok/s · LM Studio · Trusted reference	llama.cpp	Fits	6.1 GB	39k	Estimated	$499	8bit is the current best practical quantization. 4.1 tok/s is estimated from nearby benchmark coverage. 6.1 GB headroom remains at this quantization.
28	MacBook Air M4 16GB 13-inch	88	8bit	4.1 tok/s Fastest evidence path: Q4_K_M · 72.0 tok/s · LM Studio · Trusted reference	llama.cpp	Fits	6.1 GB	39k	Estimated	$1,099	8bit is the current best practical quantization. 4.1 tok/s is estimated from nearby benchmark coverage. 6.1 GB headroom remains at this quantization.
29	MacBook Air M4 16GB 15-inch	88	8bit	4.1 tok/s Fastest evidence path: Q4_K_M · 72.0 tok/s · LM Studio · Trusted reference	llama.cpp	Fits	6.1 GB	39k	Estimated	$1,299	8bit is the current best practical quantization. 4.1 tok/s is estimated from nearby benchmark coverage. 6.1 GB headroom remains at this quantization.

Qwen3.5-9B Apple Silicon benchmark and best Macs

Start with the ranked Mac table above, then audit tokens per second, RAM fit, quantization, runtimes, and source links before trusting the model on your Mac.

Quantizations observed: 4bit, Q4_K - Medium, Q8_0, Q4_0, Q4_K - Small, Q6_K

13Benchmark rows

9Chip tiers covered

106.0Fastest avg tok/s (M3 Ultra (256 GB))

5.1 GBMinimum RAM observed

Quick take

Fastest published result is 106.0 tok/s on M3 Ultra (256 GB) at 4bit. Smallest published fit is 5.1 GB on M3 Ultra (256 GB). Published runtimes include llama.cpp, LM Studio, MLX, Ollama. Start with Rankings for the decision, then use the raw rows below to audit the evidence.

Based on 13 external benchmarks; no lab runs yet.

Published runtimes: llama.cpp, LM Studio, MLX, Ollama.

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

Best Mac shortlist

These are ranked by the fastest published Qwen3.5-9B result available for each Mac's chip family. Use them as the search answer, then open the machine page before buying.

Fastest published Mac-family result

Mac Studio M3 Ultra 96GB maps to 106.0 tok/s from the strongest published chip-family row for Qwen3.5-9B.

Open Mac Studio M3 Ultra 96GB · Audit evidence

Shortlist rank 2

Mac Studio M3 Ultra 256GB maps to 106.0 tok/s from the strongest published chip-family row for Qwen3.5-9B.

Open Mac Studio M3 Ultra 256GB · Audit evidence

Shortlist rank 3

MacBook Pro M5 Max 128GB 16-inch maps to 105.0 tok/s from the strongest published chip-family row for Qwen3.5-9B.

Open MacBook Pro M5 Max 128GB 16-inch · Audit evidence

Model search answers

How fast is Qwen3.5-9B on Mac?

Qwen3.5-9B currently has a fastest published Mac result of 106.0 tok/s on M3 Ultra (256 GB) at 4bit. Check the raw rows on this page before comparing that number to a different runtime, quantization, or context length.

What is the best Mac for Qwen3.5-9B?

Mac Studio M3 Ultra 96GB is the fastest published Mac-family answer for Qwen3.5-9B on this page right now, at 106.0 tok/s from its chip family. Treat that as a published benchmark starting point, not a universal buying recommendation.

Does Qwen3.5-9B fit on Apple Silicon?

Qwen3.5-9B has a smallest published fit of 5.1 GB on M3 Ultra (256 GB). More memory may still be required for longer context, different quantization, or parallel workloads.

Catalog record

9BTotal params

DenseActive params

262,144Context window

2026-02-27Release 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

agentscodingvisual-understanding

Runtime support mentioned

vLLMSGLangTransformersKTransformers

Official specs

Type: Causal Language Model with Vision Encoder.
Scale: 9B.
Context: 262,144 natively and extensible up to 1,010,000 tokens.
Total parameters: 9B.
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

Qwen3.5-9B: 5 Apple Silicon field reports; best reported generation ~106 tok/s; seen on Mac Studio M3 ULTRA 256GB, MacBook M1 PRO 16GB, MacBook Pro M5 PRO 64GB; via MLX, llama.cpp, LM Studio.

13Benchmark rows

5Field reports

7Practitioner signals

Sparse BenchmarksEvidence status

What practitioners keep saying

The benchmark write-up recommends Qwen3.5-9B GGUF Q4_0 through llama.cpp on a 16GB Mac Mini M4 at 4.0 tok/s, 24.6 composite quality, and 58% non-reasoning MMLU.
The same thread argues that Qwen3.5-9B works better as a compact context-reading or knowledge model than as a broad local agent default on 16GB hardware.
The HomeSec-Bench page reports Qwen3.5-9B Q4_K_M on a MacBook Pro M5 Pro 64GB with llama.cpp at about 25 tok/s generation and about 0.765s TTFT.

Apple Silicon field sources

r/LocalLLaMA
2026-03-26 · Mac Mini M4 16GB · llama.cpp
A broad 16GB Mac Mini M4 sweep says Qwen3.5-9B is still one of the few dense Qwen3.5 sizes worth considering on constrained Apple Silicon, but only if you are honest about its role.
SharpAI HomeSec-Bench
2026-03-26 · MacBook Pro M5 Pro 64GB · llama.cpp
A domain benchmark on M5 Pro 64GB says Qwen3.5-9B is not just a tiny fallback model on Apple Silicon: it stays fast enough to be a serious local agent candidate.
r/LocalLLaMA
2026-03-12 · 12GB VRAM local workstation · Kilo Code or Roo Code
Practitioner testing suggests Qwen3.5-9B is unexpectedly good for agentic coding at small-model hardware limits.
r/LocalLLaMA
2026-03-05 · M1 Pro MacBook 16GB · Ollama
Qwen3.5-9B is already being used as a real agent on 16GB Apple Silicon laptops, not just demoed in chat.
r/LocalLLaMA
2026-03-04 · Mac Studio M3 Ultra 256GB · MLX
Qwen3.5-9B now has a clean high-end Apple Silicon reference as a genuinely useful small model, not just a fallback.

1 more Apple Silicon field source tracked in the research queue.

Runtime mentions in the field

Kilo Codellama.cppLM StudioMLXOllamaRoo Code

Hardware mentioned in reports

16GB64GBM1 ProM3 UltraM4MacMac MiniMac Studio

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 (64 GB), M4 Pro (24 GB), M5 Max (128 GB), M4 (16 GB) plus 4 more chip tiers. Fastest published row is 106.0 tok/s on M3 Ultra (256 GB) at 4bit. Lowest published RAM requirement is 5.1 GB on M3 Ultra (256 GB).

M3 Ultra (256 GB)M5 Max (64 GB)M4 Pro (24 GB)M5 Max (128 GB)M4 (16 GB)M3 (16 GB)M1 (16 GB)M1 Pro (16 GB)

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

Standardized eval scorecards for Qwen3.5-9B

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 71%

83%Tools

70%Coding

60%Reasoning

70%General

Speed and memory

Long decode: 106.4 tok/s
Short decode: 35.4 tok/s
Cold TTFT: 0.228 s
Active RAM: 5.1 GB

The smallest model in this set that still looks broadly useful for agent-style work.

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

Raw benchmark rows for Qwen3.5-9B

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	5.1 GB	—	106.0 tok/s	—	MLX	ref
M5 Max (64 GB)	Q4_K - Medium	—	—	105.0 tok/s	—	Ollama	ref
M4 Pro (24 GB)	Q4_K - Medium	—	—	92.0 tok/s	—	MLX	ref
M5 Max (128 GB)	Q8_0	—	—	78.0 tok/s	—	MLX	ref
M4 (16 GB)	Q4_K - Medium	—	—	72.0 tok/s	—	LM Studio	ref
M3 (16 GB)	Q4_K - Medium	—	—	58.0 tok/s	—	Ollama	ref
M1 (16 GB)	Q4_K - Medium	—	—	35.0 tok/s	—	Ollama	ref
M1 Pro (16 GB)	4bit	—	—	30.0 tok/s	—	MLX	ref
M5 Pro (64 GB)	Q4_K - Medium	13.8 GB	—	25.0 tok/s	—	llama.cpp	ref
M1 Pro (16 GB)	4bit	—	—	15.0 tok/s	—	llama.cpp	ref
M4 (16 GB)	Q4_0	—	—	4.1 tok/s	—	llama.cpp	ref
M4 (16 GB)	Q4_K - Small	—	—	3.1 tok/s	—	llama.cpp	ref
M4 (16 GB)	Q6_K	—	—	2.2 tok/s	—	llama.cpp	ref

Chips with published results for Qwen3.5-9B

M3 Ultra (256 GB)M5 Max (64 GB)M4 Pro (24 GB)M5 Max (128 GB)M4 (16 GB)M3 (16 GB)M1 (16 GB)M1 Pro (16 GB)M5 Pro (64 GB)

Data

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

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