zephyr 7b beta Mistral 7B Instruct v0.2 needs ~7.5 GB VRAM. RTX 3500 Ada Laptop 12GB has 12.0 GB. With Q4_K_M quantization, expect ~57 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
57.4 tok/s
TTFT
3370 ms
Safe context
104K
Memory
7.5 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 | 57.4 tok/s | 1838 ms | 104K |
| Coding | C | Runs well | 57.4 tok/s | 3370 ms | 104K |
| Agentic Coding | C | Runs well | 57.4 tok/s | 4902 ms | 104K |
| Reasoning | C | Runs well | 57.4 tok/s | 3983 ms | 104K |
| RAG | C | Runs well | 57.4 tok/s | 6128 ms | 104K |
How zephyr 7b beta Mistral 7B Instruct v0.2 (7B params) fits at each quantization level on RTX 3500 Ada Laptop 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | C48 |
Q3_K_S | 3 | 3.4 GB | Low | C49 |
NVFP4 | 4 |
Copy-paste commands to run zephyr 7b beta Mistral 7B Instruct v0.2 on your machine.
Run
lms load hf-maziyarpanahi--zephyr-7b-beta-mistral-7b-instruct-v0-2-gguf && lms server startYes, RTX 3500 Ada Laptop 12GB can run zephyr 7b beta Mistral 7B Instruct v0.2 with a C grade (Runs well). Expected decode speed: 57.4 tok/s.
zephyr 7b beta Mistral 7B Instruct v0.2 (7B parameters) requires approximately 7.5 GB of memory with Q4_K_M quantization.
The recommended quantization for zephyr 7b beta Mistral 7B Instruct v0.2 is Q4_K_M, which balances quality and memory efficiency.
On RTX 3500 Ada Laptop 12GB, zephyr 7b beta Mistral 7B Instruct v0.2 achieves approximately 57.4 tokens per second decode speed with a time-to-first-token of 3370ms using Q4_K_M quantization.
For coding workloads, zephyr 7b beta Mistral 7B Instruct v0.2 on RTX 3500 Ada Laptop 12GB receives a C grade with 57.4 tok/s and 104K context.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-maziyarpanahi--zephyr-7b-beta-mistral-7b-instruct-v0-2-gguf-on-rtx-3500-ada-laptop-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
3.9 GB |
| Medium |
| C50 |
Q4_K_M | 4 | 4.3 GB | Medium | C51 |
Q5_K_M | 5 | 5.0 GB | High | C52 |
Q6_K | 6 | 5.7 GB | High | C52 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | C51 |
F16 | 16 | 14.3 GB | Maximum | F0 |
On RTX 3500 Ada Laptop 12GB, zephyr 7b beta Mistral 7B Instruct v0.2 can safely use up to 104K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.