Apple M3 Max
128 GB decides what fits. 400 GB/s decides how fast it runs once it does.
Computed for 128 GB, the largest configuration. The Apple M3 Max is also sold with 36, 48, 64 or 96 GB, and what fits changes with it; some configurations also have less bandwidth, listed below.
Run it with 36 GB (300 GB/s) →Run it with 48 GB (400 GB/s) →Run it with 64 GB (400 GB/s) →Run it with 96 GB (300 GB/s) →
Open in the calculator →Best models for 128 GB, on every card that size →
Find one: Amazon ↗ · eBay (new and used) ↗Store links may pay us a commission. They never decide which card is suggested — the memory arithmetic does.
- Largest popular model that fitsQwen3.8-Flash-Next180B params · Q4_K_M · needs 111.6 GB~65 tok/s Faster than you readOpen in the calculator →
- Most downloaded that fitsQwen3.8-27B28B params · Q4_K_M · needs 18.6 GB~22 tok/s About reading paceOpen in the calculator →
At 8,192 tokens of context with the whole model in device memory. Speeds are estimates from memory bandwidth, not benchmarks run on this card.
248 of 320 fit entirely
248 of the 320 models the engine can size fit entirely in device memory at Q4_K_M where it is published, otherwise the nearest published format, and 8,192 tokens. Unified memory is one pool, so there is no second memory tier to spill into; the remaining 72 do not run at this context.
Featured models · Q4_K_M at 8,192 tokens, including offload
| Model | Needs | Verdict | Decode | Calculator |
|---|---|---|---|---|
| Qwen3.5-2B2.3B parameters | 2.32 GB | fits | ~111 tok/s | Open → |
| NVIDIA-Nemotron-3-Nano-4B-BF164.0B parameters | 3.46 GB | fits | ~78 tok/s | Open → |
| Qwen3-VL-8B-Instruct8.8B parameters | 7.04 GB | fits | ~47 tok/s | Open → |
| Qwen3.5-9B9.7B parameters | 7.05 GB | fits | ~54 tok/s | Open → |
| gemma-4-12B-it12B parameters | 9.54 GB | fits | ~36 tok/s | Open → |
| gpt-oss-20b21B parameters | 13.8 GB | fits | ~81 tok/s | Open → |
| Qwen3.8-27B28B parameters | 18.6 GB | fits | ~22 tok/sAbout reading pace | Open → |
| Qwen3.6-27B28B parameters | 18.6 GB | fits | ~22 tok/sAbout reading pace | Open → |
| Kimi-Linear-48B-A3B-Instruct49B parameters | 30.4 GB | fits | ~94 tok/s | Open → |
| Qwen3.8-Flash-Next180B parameters | 111.6 GB | fits | ~65 tok/s | Open → |
| DeepSeek-V4-Flash-Vision-Exp305B parameters | 188.1 GB | short by 60.1 GB | does not run | Open → |
| GLM-5.3-Flash321B parameters | 198.3 GB | short by 70.3 GB | does not run | Open → |
These examples are selected from prominent labs using the catalogue’s latest Hugging Face 30-day downloads and repository-creation freshness signal, with newer releases guaranteed a place. Offloaded rows assume 32 GB of system RAM, and a speed is only shown for a row that runs. Fitting in memory is not the same as loading: whether the runtime and version you have supports each architecture and format on this machine has not been tested here. Each “Open” link carries the same model, format, context and RAM into the calculator.
Fits entirely in Apple M3 Max (M3 Max 16-core CPU / 40-core GPU, 128 GB) memory — 248 of 320 sized models
The most demanding model that fits is Step-3.5-Flash at Q4_K_M: 127.0 GB of the 128 GB, leaving 1.03 GB spare.
Fully resident at 8,192 tokens (or the model’s own maximum, where that is shorter), offload off, at 400 GB/s. Each row is a run of the engine for this configuration; the rows start with current, prominent releases and “fits” is memory, not a tested runtime. Older or less prominent models remain available through this search and “Show all”.
Showing 40 of 248 models that fit.
| Model | Format | Needs | Spare | Decode | Downloads / 30d | Calculator |
|---|---|---|---|---|---|---|
| Qwen3.8-27BQwen · 28B params | Q4_K_M | 18.6 GB | 109.4 GB | ~22 tok/sAbout reading pace | 6.9M | Open → |
| Qwen3.8-Flash-NextNEWQwen · 180B params | Q4_K_M | 111.6 GB | 16.4 GB | ~65 tok/s | 1.4M | Open → |
| gemma-4-26B-A4B-itGoogle · 26B params | Q4_K_M | 16.8 GB | 111.2 GB | ~78 tok/s | 13M | Open → |
| gemma-4-31B-itGoogle · 31B params | Q4_K_M | 22.2 GB | 105.8 GB | ~16 tok/sAbout reading pace | 9.9M | Open → |
| Qwen3.5-9BQwen · 9.7B params | Q4_K_M | 7.05 GB | 121.0 GB | ~54 tok/s | 9M | Open → |
| Qwen3.5-4BQwen · 4.7B params | Q4_K_M | 3.98 GB | 124.0 GB | ~78 tok/s | 7.8M | Open → |
| Qwen3.6-35B-A3BQwen · 36B params | Q4_K_M | 23.1 GB | 104.9 GB | ~94 tok/s | 3.3M | Open → |
| gemma-4-12B-itGoogle · 12B params | Q4_K_M | 9.54 GB | 118.5 GB | ~36 tok/s | 1.9M | Open → |
| Qwen3.6-27BQwen · 28B params | Q4_K_M | 18.6 GB | 109.4 GB | ~22 tok/sAbout reading pace | 2.5M | Open → |
| Qwen3.5-2BQwen · 2.3B params | Q4_K_M | 2.32 GB | 125.7 GB | ~111 tok/s | 4.9M | Open → |
| gemma-4-E4B-itGoogle · 8.0B params | Q4_K_M | 5.86 GB | 122.1 GB | ~73 tok/s | 4.4M | Open → |
| NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16NVIDIA · 32B params | Q4_K_M | 20.3 GB | 107.7 GB | ~17 tok/sAbout reading pace | 530K | Open → |
| NVIDIA-Nemotron-3-Nano-4B-BF16NVIDIA · 4.0B params | Q4_K_M | 3.46 GB | 124.5 GB | ~78 tok/s | 3.4M | Open → |
| gemma-4-E2B-itGoogle · 5.1B params | Q4_K_M | 4.02 GB | 124.0 GB | ~114 tok/s | 3M | Open → |
| Qwen3.5-0.8BQwen · 873M params | Q4_K_M | 1.46 GB | 126.5 GB | ~139 tok/s | 2.6M | Open → |
| Qwen3-VL-8B-InstructQwen · 8.8B params | Q4_K_M | 7.04 GB | 121.0 GB | ~47 tok/s | 14.6M | Open → |
| Qwen3.5-27BQwen · 28B params | Q4_K_M | 18.6 GB | 109.4 GB | ~22 tok/sAbout reading pace | 1.9M | Open → |
| North-Micro-Vision-InstructCohereLabs · 2.5B params | Q4_K_M | 2.99 GB | 125.0 GB | ~94 tok/s | 180.7K | Open → |
| Qwen3.5-35B-A3BQwen · 36B params | Q4_K_M | 23.1 GB | 104.9 GB | ~94 tok/s | 1.6M | Open → |
| NVIDIA-Nemotron-3-Super-120B-A12B-BF16NVIDIA · 124B params | Q4_K_M | 76.9 GB | 51.1 GB | ~4.8 tok/sSlow | 1.2M | Open → |
| granite-4.2-8bIBM · 8.8B params | Q4_K_M | 7.49 GB | 120.5 GB | ~44 tok/s | 128.4K | Open → |
| GLM-4.7-Flashzai-org · 31B params | Q4_K_M | 20.4 GB | 107.6 GB | ~17 tok/sAbout reading pace | 1.8M | Open → |
| granite-4.1-3bIBM · 3.4B params | Q4_K_M | 3.72 GB | 124.3 GB | ~76 tok/s | 521.8K | Open → |
| LFM2.5-2.6BLiquidAI · 2.7B params | Q4_K_M | 2.61 GB | 125.4 GB | ~97 tok/s | 108.1K | Open → |
| Qwen3-VL-4B-InstructQwen · 4.4B params | Q4_K_M | 4.72 GB | 123.3 GB | ~64 tok/s | 3.5M | Open → |
| granite-4.1-30bIBM · 29B params | Q4_K_M | 20.4 GB | 107.6 GB | ~17 tok/sAbout reading pace | 301.5K | Open → |
| Qwen3.5-122B-A10BQwen · 125B params | Q4_K_M | 77.9 GB | 50.1 GB | ~52 tok/s | 512.6K | Open → |
| Qwen3-VL-2B-InstructQwen · 2.1B params | Q4_K_M | 3.05 GB | 125.0 GB | ~90 tok/s | 2.8M | Open → |
| granite-4.2-3bIBM · 3.7B params | Q4_K_M | 3.72 GB | 124.3 GB | ~76 tok/s | 50.6K | Open → |
| LFM2.5-230MLiquidAI · 230M params | Q4_K_M | 1.05 GB | 126.9 GB | ~158 tok/s | 88.6K | Open → |
| Qwen3-0.6BQwen · 752M params | Q4_K_M | 2.22 GB | 125.8 GB | ~108 tok/s | 29.7M | Open → |
| Qwen3-Coder-NextQwen · 80B params | Q4_K_M | 50.0 GB | 78.0 GB | ~76 tok/s | 596.3K | Open → |
| gpt-oss-20bOpenAI · 21B params | Q4_K_M | 13.8 GB | 114.2 GB | ~81 tok/s | 6.6M | Open → |
| granite-4.2-30bIBM · 29B params | Q4_K_M | 20.7 GB | 107.3 GB | ~17 tok/sAbout reading pace | 35.8K | Open → |
| granite-4.1-8bIBM · 8.8B params | Q4_K_M | 7.49 GB | 120.5 GB | ~44 tok/s | 179.3K | Open → |
| NVIDIA-Nemotron-3-Nano-30B-A3B-BF16NVIDIA · 32B params | Q4_K_M | 20.3 GB | 107.7 GB | ~17 tok/sAbout reading pace | 875.2K | Open → |
| gpt-oss-120bOpenAI · 117B params | Q4_K_M | 71.9 GB | 56.1 GB | ~66 tok/s | 4.5M | Open → |
| LFM2.5-VL-3BLiquidAI · 3.1B params | Q4_K_M | 2.85 GB | 125.1 GB | ~97 tok/s | 26.7K | Open → |
| MiMo-V2.6-Distill-Qwen-9BNEWXiaomiMiMo · 9.4B params | Q4_K_M | 6.90 GB | 121.1 GB | ~54 tok/s | 14.6K | Open → |
| Qwen3-4B-Instruct-2507Qwen · 4.0B params | Q4_K_M | 4.72 GB | 123.3 GB | ~64 tok/s | 3.7M | Open → |
Sized at the format most people actually download, not at FP16. The catalogue ordered by downloads →
Find the Apple M3 Max: Amazon ↗ · eBay (new and used) ↗Store links may pay us a commission. They never decide which card is suggested — the memory arithmetic does.
The Apple M3 Max, model by model
One page per model: whether it fits this device, at which formats, and how fast.
- Qwen3-0.6B
- Qwen3-VL-8B-Instruct
- gemma-4-26B-A4B-it
- Qwen3-8B
- gemma-4-31B-it
- Qwen3.5-9B
- Qwen2.5-0.5B-Instruct
- Qwen2.5-7B-Instruct
- Qwen3.5-4B
- Qwen3-4B
- Qwen2.5-1.5B-Instruct
- Qwen3.8-27B
All 70Fewer
- gpt-oss-20b
- Qwen2.5-VL-7B-Instruct
- GLM-5.3-Flash
- Qwen3.5-2B
- dolphin-2.9.1-yi-1.5-34b
- DeepSeek-V4-Flash-0731
- gpt-oss-120b
- gemma-4-E4B-it
- Qwen2.5-3B-Instruct
- Qwen3-32B
- Qwen3-4B-Instruct-2507
- DeepSeek-V3.2
- Qwen3-VL-4B-Instruct
- pythia-160m
- NVIDIA-Nemotron-3-Nano-4B-BF16
- Qwen3.6-35B-A3B
- Qwen3-1.7B
- gemma-4-E2B-it
- OTel-2.0-LLM-31B-IT
- Qwen3-VL-2B-Instruct
- Qwen3-14B
- Qwen3.5-0.8B
- JiRackUltra_1b
- Qwen3.6-27B
- Qwen2.5-VL-3B-Instruct
- Qwen2.5-Coder-7B-Instruct
- Mistral-7B-Instruct-v0.3
- Qwen2.5-32B-Instruct
- gemma-4-12B-it
- Qwen3.5-27B
- SmolLM2-135M-Instruct
- SmolLM2-135M
- GLM-4.7-Flash
- Mistral-7B-Instruct-v0.2
- Qwen2.5-Coder-14B-Instruct
- Qwen2.5-14B-Instruct
- Qwen3.5-35B-A3B
- Qwen3-30B-A3B
- Qwen2.5-0.5B
- Ornith-1.0-35B
- pythia-70m-deduped
- DeepSeek-V3-0324
- Qwen3.8-Flash-Next
- GLM-5.3
- TinyLlama-1.1B-Chat-v1.0
- DeepSeek-V3
- Kimi-K3
- NVIDIA-Nemotron-3-Super-120B-A12B-BF16
- MiniMax-M2.7
- DeepSeek-V4-Flash
- MiniCPM5-2B
- DeepSeek-R1
- DeepSeek-R1-Distill-Qwen-1.5B
- Ornith-1.0-9B
- DeepSeek-V4-Flash-Vision-Exp
- DeepSeek-Coder-V2-Lite-Instruct
- Qwen2.5-Coder-32B-Instruct
- NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
The specification behind every figure
What the manufacturer publishes for this device, and the pages it was read from.
Manufacturer specification
| Memory scope | unified-system |
|---|---|
| Capacity | 128 GB |
| Published options | 36 GB, 48 GB, 64 GB, 96 GB, 128 GB |
| Bandwidth | 400 GB/s |
| Memory type | unified memory |
| Bus width | Not published |
| FP32 peak | Not published |
| Dense matrix peak | Not published without sparsity |
| Power | Not published |
Source ledger
Caveats
- The flat bandwidth/capacity fields are maxima; configurations preserve Apple's exact CPU/GPU and bandwidth/capacity groupings. No VRAM capacity is claimed.
Official configurations
| Configuration | GPU cores | Memory | Bandwidth |
|---|---|---|---|
| M3 Max 14-core CPU / 30-core GPU | 30 | 36 / 96 GB | 300 GB/s |
| M3 Max 16-core CPU / 40-core GPU | 40 | 48 / 64 / 128 GB | 400 GB/s |
Published capacity is a hardware ceiling, not guaranteed free runtime memory. The calculator shows the runtime reserve separately rather than folding it into a single number.
Run the diagnostic on the Apple M3 Max →