Canonical Rankings

Best Macs for this model

Qwen3.5-35B-A3B ranked across the Mac lineup at the best practical quantization, using the best available runtime evidence.

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

Rank	Mac	Score	Quant	Tok/s	Runtime	Fits	Evidence	Price	Why it ranks here
1	Mac Studio M3 Ultra 256GB	616	8bit	80.0 tok/s	MLX	Fits	Measured	$7,499	8bit is the current best practical quantization. 80.0 tok/s is directly measured here. 222.3 GB headroom remains at this quantization.
2	Mac Pro M2 Ultra 192GB	544	8bit	80.0 tok/s	MLX	Fits	Estimated	$6,999	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 158.3 GB headroom remains at this quantization.
3	Mac Studio M4 Max 128GB	480	8bit	80.0 tok/s	MLX	Fits	Estimated	$4,499	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 94.3 GB headroom remains at this quantization.
4	MacBook Pro M4 Max 128GB 16-inch	480	8bit	80.0 tok/s	MLX	Fits	Estimated	$5,999	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 94.3 GB headroom remains at this quantization.
5	Mac Studio M3 Ultra 96GB	448	8bit	80.0 tok/s	MLX	Fits	Estimated	$3,999	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 62.3 GB headroom remains at this quantization.
6	Mac Studio M4 Max 64GB	416	8bit	80.0 tok/s	MLX	Fits	Estimated	$2,999	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 30.3 GB headroom remains at this quantization.
7	MacBook Pro M4 Max 64GB 16-inch	416	8bit	80.0 tok/s	MLX	Fits	Estimated	$4,499	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 30.3 GB headroom remains at this quantization.
8	Mac Mini M4 Pro 48GB	400	8bit	80.0 tok/s	MLX	Fits	Estimated	$1,599	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 14.3 GB headroom remains at this quantization.
9	MacBook Pro M4 Pro 48GB 14-inch	400	8bit	80.0 tok/s	MLX	Fits	Estimated	$2,499	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 14.3 GB headroom remains at this quantization.
10	Mac Studio M4 Max 48GB	400	8bit	80.0 tok/s	MLX	Fits	Estimated	$2,499	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 14.3 GB headroom remains at this quantization.
11	MacBook Pro M4 Pro 48GB 16-inch	400	8bit	80.0 tok/s	MLX	Fits	Estimated	$2,999	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 14.3 GB headroom remains at this quantization.
12	MacBook Pro M4 Max 48GB 14-inch	400	8bit	80.0 tok/s	MLX	Fits	Estimated	$3,499	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 14.3 GB headroom remains at this quantization.
13	MacBook Pro M4 Max 48GB 16-inch	400	8bit	80.0 tok/s	MLX	Fits	Estimated	$3,999	8bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 14.3 GB headroom remains at this quantization.
14	Mac Studio M4 Max 36GB	388	Q6_K	80.0 tok/s	MLX	Fits	Estimated	$1,999	Q6_K is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 8.1 GB headroom remains at this quantization.
15	MacBook Pro M4 Max 36GB 14-inch	388	Q6_K	80.0 tok/s	MLX	Fits	Estimated	$2,999	Q6_K is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 8.1 GB headroom remains at this quantization.
16	MacBook Pro M4 Max 36GB 16-inch	388	Q6_K	80.0 tok/s	MLX	Fits	Estimated	$3,499	Q6_K is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 8.1 GB headroom remains at this quantization.
17	Mac Mini M4 32GB	386	6bit	80.0 tok/s	MLX	Fits	Estimated	$799	6bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 6.4 GB headroom remains at this quantization.
18	MacBook Air M4 32GB 13-inch	386	6bit	80.0 tok/s	MLX	Fits	Estimated	$1,499	6bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 6.4 GB headroom remains at this quantization.
19	MacBook Air M4 32GB 15-inch	386	6bit	80.0 tok/s	MLX	Fits	Estimated	$1,699	6bit is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 6.4 GB headroom remains at this quantization.
20	Mac Mini M4 24GB	378	Q4_K_M	80.0 tok/s	MLX	Fits	Estimated	$599	Q4_K_M is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.
21	MacBook Air M4 24GB 13-inch	378	Q4_K_M	80.0 tok/s	MLX	Fits	Estimated	$1,299	Q4_K_M is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.
22	Mac Mini M4 Pro 24GB	378	Q4_K_M	80.0 tok/s	MLX	Fits	Estimated	$1,399	Q4_K_M is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.
23	MacBook Air M4 24GB 15-inch	378	Q4_K_M	80.0 tok/s	MLX	Fits	Estimated	$1,499	Q4_K_M is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.
24	MacBook Pro M4 Pro 24GB 14-inch	378	Q4_K_M	80.0 tok/s	MLX	Fits	Estimated	$1,999	Q4_K_M is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.
25	MacBook Pro M4 Pro 24GB 16-inch	378	Q4_K_M	80.0 tok/s	MLX	Fits	Estimated	$2,499	Q4_K_M is the current best practical quantization. 80.0 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.
26	Mac Mini M4 16GB	33	Q2_K	1.3 tok/s	llama.cpp	Fits	Estimated	$499	Q2_K is the current best practical quantization. 1.3 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.
27	MacBook Air M4 16GB 13-inch	33	Q2_K	1.3 tok/s	llama.cpp	Fits	Estimated	$1,099	Q2_K is the current best practical quantization. 1.3 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.
28	MacBook Air M4 16GB 15-inch	33	Q2_K	1.3 tok/s	llama.cpp	Fits	Estimated	$1,299	Q2_K is the current best practical quantization. 1.3 tok/s is estimated from nearby benchmark coverage. 4.2 GB headroom remains at this quantization.

Qwen3.5-35B-A3B — 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, Q4_K - Medium, 8bit, Q4_K_L

7Benchmark rows

5Chip tiers covered

128.0Fastest avg tok/s (M5 Max (48 GB))

19.6 GBMinimum RAM observed

What this page answers best

Fastest published result is 128.0 tok/s on M5 Max (48 GB) at 4bit. Smallest published fit is 19.6 GB on M3 Ultra (256 GB). Longest published context on this page is 8k. Published runtimes include llama.cpp, MLX. Start with Rankings for the decision, then use the raw rows below to audit the evidence.

Evidence state: 7 linked reference rows and no Silicon Score Lab rows yet.

Published runtimes here: 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

35BTotal params

3BActive 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 takeaways

Type: Causal Language Model with Vision Encoder.
Scale: 35B in total and 3B activated.
Context: 262,144 natively and extensible up to 1,010,000 tokens..
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…

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

Field reality on Apple Silicon

Qwen3.5-35B-A3B: 11 Apple Silicon field reports; best reported generation ~89.4 tok/s; seen on MacBook Pro M1 MAX 64GB, Mac Mini M4 PRO 64GB, Apple Silicon; via llama.cpp, MLX, Ollama.

7Benchmark rows

11Field reports

8Practitioner signals

Sparse BenchmarksEvidence status

What practitioners keep saying

MLX is reported as dramatically improving Apple Silicon usability versus weaker default runtime paths.
This model should be treated as a real local contender, not just a spec-sheet curiosity.
The reported upgrade is operational, not academic: fewer model swaps and better end-to-end usefulness.

Runtime mentions in the field

Claude CodeContinuellama.cppLM StudioMLXOllama

Hardware mentioned in reports

16GB32GB48GB64GB128GBM1 MaxM1 UltraM4

What would improve confidence

Capture Practitioner Runtime Notes
Queue Lab Verification If Hardware Available
Reproduce Field Performance Signal
Upgrade To First Party Measurement

Current published coverage

Published chip coverage includes M5 Max (48 GB), M3 Ultra (256 GB), M1 Max (64 GB), M5 Pro (64 GB), M4 (16 GB). Fastest published row is 128.0 tok/s on M5 Max (48 GB) at 4bit. Lowest published RAM requirement is 19.6 GB on M3 Ultra (256 GB). Catalog context window is 8k.

M5 Max (48 GB)M3 Ultra (256 GB)M1 Max (64 GB)M5 Pro (64 GB)M4 (16 GB)

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

Standardized eval scorecards for Qwen3.5-35B-A3B

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 74%

87%Tools

90%Coding

50%Reasoning

70%General

Speed and memory

Long decode: 95.2 tok/s
Short decode: 31.7 tok/s
Cold TTFT: 0.322 s
Active RAM: 19.6 GB

Very fast for its size, but reasoning softness is visible in the standardized tasks.

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

8bit · vLLM-MLX

Mac Studio M3 Ultra 256GB · Avg 85%

90%Tools

90%Coding

80%Reasoning

80%General

Speed and memory

Long decode: 80.0 tok/s
Short decode: 32.4 tok/s
Cold TTFT: 0.456 s
Active RAM: 36.9 GB

The stronger version of the 35B MoE story: fast and much more balanced.

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

Workflow runtime comparisons for Qwen3.5-35B-A3B

These are same-model runtime comparisons on Apple Silicon that capture effective throughput and prefill-heavy behavior. They help explain runtime choice, but they do not replace canonical decode-speed benchmark rows.

Ops agent (8 turns)

MacBook Pro M1 Max 64GB · Effective tok/s · Interactive

Best runtime observed: oMLX (38.0)

Spread to next result: 2.4 tok/s

Runtime results

oMLX — 38.0 tok/s · Best reported runtime on this workload.
Rapid-MLX — 35.6 tok/s
mlx-openai-server — 26.2 tok/s
LM Studio (GGUF) — 17.6 tok/s · GGUF reference from the same article.
LM Studio (MLX) — 17.0 tok/s · Slowest MLX wrapper in this comparison.

Famstack runtime benchmark writeup · 2026-03-20

These are effective throughput results on an ops-agent workflow. They are best used to compare runtime behavior and caching quality on Apple Silicon, not to replace canonical decode-speed rows.

Prefill stress (8K context)

MacBook Pro M1 Max 64GB · Effective tok/s · 8,000 ctx

Best runtime observed: oMLX (16.4)

Spread to next result: 7.7 tok/s

Runtime results

oMLX — 16.4 tok/s · Best reported runtime in this scenario.
mlx-openai-server — 8.7 tok/s
Rapid-MLX — 8.5 tok/s
LM Studio (GGUF) — 7.8 tok/s
LM Studio (MLX) — 5.9 tok/s

Famstack runtime benchmark writeup · 2026-03-20

This is an 8K prefill-stress comparison. It is useful for understanding caching and long-context behavior, not for headline decode-speed ranking.

Raw benchmark rows for Qwen3.5-35B-A3B

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
M5 Max (48 GB)	4bit	—	8k	128.0 tok/s	3235.0 tok/s	MLX	ref
M3 Ultra (256 GB)	4bit	19.6 GB	—	95.0 tok/s	—	MLX	ref
M5 Max (48 GB)	Q4_K - Medium	—	8k	89.4 tok/s	783.0 tok/s	llama.cpp	ref
M3 Ultra (256 GB)	8bit	36.9 GB	—	80.0 tok/s	—	MLX	ref
M1 Max (64 GB)	4bit	—	8k	57.6 tok/s	431.0 tok/s	MLX	ref
M5 Pro (64 GB)	Q4_K_L	27.2 GB	—	41.9 tok/s	—	llama.cpp	ref
M4 (16 GB)	Q4_K - Medium	—	—	1.3 tok/s	—	llama.cpp	ref

Chips with published results for Qwen3.5-35B-A3B

M5 Max (48 GB)M3 Ultra (256 GB)M1 Max (64 GB)M5 Pro (64 GB)M4 (16 GB)

Data

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

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