Nous Hermes 2 Mistral 7B DPO needs ~8.6 GB VRAM. MacBook Air M4 24GB has 17.3 GB. With Q4_K_M quantization, expect ~19 tok/s.
Operating mode
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
Fit status
Runs well
Decode
18.6 tok/s
TTFT
10400 ms
Safe context
186K
Memory
8.6 GB / 17.3 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 18.6 tok/s | 5673 ms | 186K |
| Coding | C | Runs well | 18.6 tok/s | 10400 ms | 186K |
| Agentic Coding | C | Runs well | 18.6 tok/s | 15127 ms | 186K |
| Reasoning | C | Runs well | 18.6 tok/s | 12291 ms | 186K |
| RAG | C | Runs well | 18.6 tok/s | 18909 ms | 186K |
How Nous Hermes 2 Mistral 7B DPO (7B params) fits at each quantization level on MacBook Air M4 24GB (17.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | C46 |
Q3_K_S | 3 | 3.4 GB | Low | C47 |
NVFP4 | 4 | 3.9 GB | Medium | C47 |
Q4_K_M | 4 | 4.3 GB | Medium | C47 |
Q5_K_M | 5 | 5.0 GB | High | C48 |
Q6_K | 6 | 5.7 GB | High | C49 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | C50 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Copy-paste commands to run Nous Hermes 2 Mistral 7B DPO on your machine.
Run
lms load hf-nousresearch--nous-hermes-2-mistral-7b-dpo-gguf && lms server start升级选项
Raises estimated decode speed by about 192%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
Raises estimated decode speed by about 254%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Raises estimated decode speed by about 177%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Yes, MacBook Air M4 24GB can run Nous Hermes 2 Mistral 7B DPO with a C grade (Runs well). Expected decode speed: 18.6 tok/s.
Nous Hermes 2 Mistral 7B DPO (7B parameters) requires approximately 8.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Nous Hermes 2 Mistral 7B DPO is Q4_K_M, which balances quality and memory efficiency.
On MacBook Air M4 24GB, Nous Hermes 2 Mistral 7B DPO achieves approximately 18.6 tokens per second decode speed with a time-to-first-token of 10400ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 2 Mistral 7B DPO on MacBook Air M4 24GB receives a C grade with 18.6 tok/s and 186K context.
On MacBook Air M4 24GB, Nous Hermes 2 Mistral 7B DPO can safely use up to 186K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. MacBook Air M4 24GB 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.
Paste this snippet into any page to show a live fit card.
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