M2 Ultra vs M3 Ultra
The highest-RAM Apple Silicon chips. Mac Studio and Mac Pro territory. Similar throughput, different memory ceilings.
Ultra chips combine two Max dies. M3 Ultra and M2 Ultra both target developers who need 192 GB+ unified memory for large model inference — running 70B, 105B, or 235B models without offloading. The generation performance difference is modest; the RAM ceiling difference is significant.
Benchmark comparison — shared models
Best published result for each model. Comparing top-spec configs: M3 Ultra 80-core GPU 256 GB vs M2 Ultra 60-core GPU 64 GB (closest common configs with data).
| Model | M2 Ultra (60-core, 64 GB) | M3 Ultra (80-core, 256 GB) | Difference |
|---|---|---|---|
| Llama 3.2 1B Instruct Q4_K - Medium |
176.4 tok/s M2 Ultra 60-core, 128 GB |
177.9 tok/s M3 Ultra 80-core, 256 GB |
+1% |
| Llama 3.1 8B Instruct Q4_K - Medium |
59.5 tok/s M2 Ultra 60-core, 64 GB |
63.3 tok/s M3 Ultra 80-core, 256 GB |
+6% |
| Qwen 2.5 14B Instruct Q4_K - Medium |
36.6 tok/s M2 Ultra 76-core, 128 GB |
36.7 tok/s M3 Ultra 80-core, 256 GB |
+0.3% |
Data source: benchmarks.json. Reference run data from LocalScore community aggregation. Direct same-config comparisons are limited; these are the closest available configs.
Chip specs compared
| Spec | M2 Ultra | M3 Ultra |
|---|---|---|
| GPU cores | 60 or 76 | 60 or 80 |
| Memory bandwidth | ~800 GB/s | ~800 GB/s |
| Max unified RAM | 192 GB | 512 GB |
| Available in | Mac Studio, Mac Pro | Mac Studio, Mac Pro |
| Can run 70B at Q4? | Yes (fits in 192 GB) | Yes (all configs) |
| Can run 235B at Q4? | No (needs ~130 GB, tight at 192 GB) | Yes (256 GB+ configs) |
| Can run 405B at Q4? | No | Yes (512 GB config) |
Memory bandwidth is similar between M2 Ultra and M3 Ultra — both achieve ~800 GB/s. The generation bump from M2 to M3 does not substantially increase inference speed. The meaningful difference is the RAM ceiling: M3 Ultra's 512 GB max vs M2 Ultra's 192 GB opens up full-precision or high-quant 405B inference.
What models can each run?
| Model | Quant | RAM needed | M2 Ultra (192 GB) | M3 Ultra (256 GB) | M3 Ultra (512 GB) |
|---|---|---|---|---|---|
| Llama 3.1 8B | Q4_K_M | ~5 GB | Yes | Yes | Yes |
| Qwen 2.5 14B | Q4_K_M | ~9 GB | Yes | Yes | Yes |
| Llama 3.3 70B | Q4_K_M | ~43 GB | Yes | Yes | Yes |
| Qwen 3 235B A22B | Q4_K_M | ~140 GB | Marginal (192 GB) | Yes | Yes |
| Llama 3.1 405B | Q4_K_M | ~245 GB | No | No (tight) | Yes |
| Llama 3.1 405B | Q8_0 | ~432 GB | No | No | Yes (512 GB) |
Who should choose which
Choose M2 Ultra if…
- You already own it — upgrade is hard to justify on speed alone
- Your largest model is 70B Q4 (~43 GB)
- 192 GB is sufficient for your model portfolio
- Price difference matters (M2 Ultra refurb is significantly cheaper)
- You run many mid-size models concurrently
Choose M3 Ultra if…
- You need to run 235B+ models without quantization tradeoffs
- You want 256 GB or 512 GB for massive context windows
- You are building a multi-model research workstation
- You want to run Llama 405B or equivalent locally
- Buying new — the RAM ceiling advantage is substantial
Verdict
On shared benchmark models, M3 Ultra is 1–6% faster than M2 Ultra — within measurement noise for most workloads. The throughput story at Ultra tier is almost entirely about memory bandwidth, which is similar across both generations (~800 GB/s). Where M3 Ultra wins decisively is the 512 GB RAM option, which enables full Q4 inference on Llama 405B and near-full-precision runs on 235B models. If you need to run models larger than 70B, M3 Ultra's higher RAM ceiling is the reason to upgrade.
Chip pages
Related comparisons
Data
benchmarks.json — full dataset · chips.json — chip summaries · benchmarks.csv — CSV export