RTX PRO 5000 Blackwell 48GBコスパ重視1344 GB/s (+798)
C
Raises estimated decode speed by about 88%.51.4 tok/sデコード
Raises estimated decode speed by about 88%.
〜$4,999 MSRP
Can Hermes 4.3 36B run on MacBook Pro M4 Max 64GB?
YES — Runs Great
C53Usable
Estimated from fit model
Hermes 4.3 36B needs ~34.0 GB VRAM. MacBook Pro M4 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~27 tok/s.
Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: StandardBottleneck: Balanced
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Q4_K_M (Medium quality) — 34.0 GB, 27.3 tok/s, Runs well
34.0 GB required46.1 GB available
74% VRAM used
Fit status
Runs well
Decode
27.3 tok/s
TTFT
7079 ms
Safe context
62K
Memory
34.0 GB / 46.1 GB
Memory breakdown
Weights22.0 GB
KV Cache4.2 GB
Runtime0.9 GB
Headroom6.9 GB
See how fast it feels
See how fast it feelsHermes 4.3 36B on MacBook Pro M4 Max 64GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 27.3 tok/s decode · 7.1s TTFT (warm) · 68 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 27.3 tok/s | 3861 ms | 62K |
| Coding | C | Runs well | 27.3 tok/s | 7079 ms | 62K |
| Agentic Coding | C | Tight fit | 27.3 tok/s | 10296 ms | 62K |
| Reasoning | C | Runs well | 27.3 tok/s | 8366 ms | 62K |
| RAG | C | Tight fit | 27.3 tok/s | 12871 ms | 62K |
Inference speed
Hermes 4.3 36B inference speed — tokens per second by GPU & Mac
Estimated decode speed (tokens/sec) for Hermes 4.3 36B at Q4_K_M across popular GPUs and Apple Silicon, including multi-GPU rigs, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~55 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
| RTX 5090 32GB | 32 GB | Q4_K_M | 54.7 | Offloads |
2× RX 7900 XTX 24GB | 48 GB | Q4_K_M | 53.5 | Fits |
| 2× RTX 4090 24GB | 48 GB | Q4_K_M | 28.1 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 27.3 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 27.3 | Fits |
| 2× RTX 3090 24GB | 48 GB | Q4_K_M | 25.8 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 25.4 | Fits |
| 4× RTX 3060 12GB | 48 GB | Q4_K_M | 22.7 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 21.1 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 20.0 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 17.2 | Tight |
| RTX 4090 24GB | 24 GB | Q4_K_M | 16.6 | Too big |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 15.3 | Too big |
| RTX 3090 24GB | 24 GB | Q4_K_M | 14.2 | Too big |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 10.9 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 10.0 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 6.0 | Too big |
| RTX 4070 12GB | 12 GB | Q4_K_M | 2.6 | Too big |
| RTX 3060 12GB | 12 GB | Q4_K_M | 2.0 | Too big |
| RTX 4060 8GB | 8 GB | Q4_K_M | 2.0 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
Quantization options
How Hermes 4.3 36B (36B params) fits at each quantization level on MacBook Pro M4 Max 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 14.0 GB | Low | C45 |
Q3_K_S | 3 | 17.6 GB | Low | C46 |
NVFP4 | 4 | 20.2 GB | Medium | C47 |
Q4_K_M | 4 | 22.0 GB | Medium | C47 |
Q5_K_M | 5 | 25.9 GB | High | C48 |
Q6_KBest for your GPU | 6 | 29.5 GB | High | C48 |
Q8_0 | 8 | 38.5 GB | Very High | F0 |
F16 | 16 | 73.8 GB | Maximum | F0 |
Get started
Copy-paste commands to run Hermes 4.3 36B on your machine.
Run
lms load hf-nousresearch--hermes-4-3-36b-gguf && lms server startアップグレードオプション
Hermes 4.3 36Bを快適に動かすハードウェア
Frequently asked questions
Can MacBook Pro M4 Max 64GB run Hermes 4.3 36B?
Yes, MacBook Pro M4 Max 64GB can run Hermes 4.3 36B with a C grade (Runs well). Expected decode speed: 27.3 tok/s.
How much VRAM does Hermes 4.3 36B need?
Hermes 4.3 36B (36B parameters) requires approximately 34.0 GB of memory with Q4_K_M quantization.
What is the best quantization for Hermes 4.3 36B?
The recommended quantization for Hermes 4.3 36B is Q4_K_M, which balances quality and memory efficiency.
What speed will Hermes 4.3 36B run at on MacBook Pro M4 Max 64GB?
On MacBook Pro M4 Max 64GB, Hermes 4.3 36B achieves approximately 27.3 tokens per second decode speed with a time-to-first-token of 7079ms using Q4_K_M quantization.
Can MacBook Pro M4 Max 64GB run Hermes 4.3 36B for coding?
For coding workloads, Hermes 4.3 36B on MacBook Pro M4 Max 64GB receives a C grade with 27.3 tok/s and 62K context.
What context window can Hermes 4.3 36B use on MacBook Pro M4 Max 64GB?
On MacBook Pro M4 Max 64GB, Hermes 4.3 36B can safely use up to 62K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Is unified memory on MacBook Pro M4 Max 64GB as fast as VRAM for Hermes 4.3 36B?
Not always. MacBook Pro M4 Max 64GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.
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