stablelm 2 zephyr 1 6b needs ~6.8 GB VRAM. RTX 4080 Laptop 12GB has 12.0 GB. With Q4_K_M quantization, expect ~84 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
84.0 tok/s
TTFT
2305 ms
Safe context
135K
Memory
6.8 GB / 12.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 84.0 tok/s | 1257 ms | 135K |
| Coding | C | Runs well | 84.0 tok/s | 2305 ms | 135K |
| Agentic Coding | C | Runs well | 84.0 tok/s | 3352 ms | 135K |
| Reasoning | C | Runs well | 84.0 tok/s | 2724 ms | 135K |
| RAG | C | Runs well | 84.0 tok/s | 4190 ms | 135K |
How stablelm 2 zephyr 1 6b (6B params) fits at each quantization level on RTX 4080 Laptop 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.3 GB | Low | C48 |
Q3_K_S | 3 | 2.9 GB | Low | C49 |
NVFP4 | 4 | 3.4 GB | Medium | C50 |
Q4_K_M | 4 | 3.7 GB | Medium | C50 |
Q5_K_M | 5 | 4.3 GB | High | C51 |
Q6_K | 6 | 4.9 GB | High | C52 |
Q8_0Best for your GPU | 8 | 6.4 GB | Very High | C52 |
F16 | 16 | 12.3 GB | Maximum | F0 |
Copy-paste commands to run stablelm 2 zephyr 1 6b on your machine.
Run
lms load hf-stabilityai--stablelm-2-zephyr-1-6b && lms server startYes, RTX 4080 Laptop 12GB can run stablelm 2 zephyr 1 6b with a C grade (Runs well). Expected decode speed: 84.0 tok/s.
stablelm 2 zephyr 1 6b (6B parameters) requires approximately 6.8 GB of memory with Q4_K_M quantization.
The recommended quantization for stablelm 2 zephyr 1 6b is Q4_K_M, which balances quality and memory efficiency.
On RTX 4080 Laptop 12GB, stablelm 2 zephyr 1 6b achieves approximately 84.0 tokens per second decode speed with a time-to-first-token of 2305ms using Q4_K_M quantization.
For coding workloads, stablelm 2 zephyr 1 6b on RTX 4080 Laptop 12GB receives a C grade with 84.0 tok/s and 135K context.
On RTX 4080 Laptop 12GB, stablelm 2 zephyr 1 6b can safely use up to 135K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-stabilityai--stablelm-2-zephyr-1-6b-on-rtx-4080-laptop-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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