Magistral 7B needs ~7.9 GB VRAM. RTX 4060 Laptop 8GB has 8.0 GB. With Q4_K_M quantization, expect ~45 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 with offload
Decode
44.5 tok/s
TTFT
4353 ms
Safe context
8K
Memory
7.9 GB / 8.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Tight fit | 44.5 tok/s | 2375 ms | 8K |
| Coding | A | Runs with offload | 44.5 tok/s | 4353 ms | 8K |
| Agentic Coding | F | Too heavy | 21.4 tok/s | 13156 ms | 8K |
| Reasoning | A | Runs with offload | 44.5 tok/s | 5145 ms | 8K |
| RAG | F | Too heavy | 21.4 tok/s | 16445 ms | 8K |
How Magistral 7B (7B params) fits at each quantization level on RTX 4060 Laptop 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | A81 |
Q3_K_S | 3 | 3.4 GB | Low | A81 |
NVFP4 | 4 | 3.9 GB | Medium | A81 |
Q4_K_M | 4 | 4.3 GB | Medium | A81 |
Q5_K_MBest for your GPU | 5 | 5.0 GB | High | A81 |
Q6_K | 6 | 5.7 GB | High | F0 |
Q8_0 | 8 | 7.5 GB | Very High | F0 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Copy-paste commands to run Magistral 7B on your machine.
Run
lms load Magistral-7B && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | A | 18.5 tok/s | |
| Qwen 3 8B | 8B | A | 24 tok/s | |
 Nemotron Nano 8B | 8B | A | 25.5 tok/s | |
 InternVL2 8B | 8B | A | 25.5 tok/s | |
 Ministral 3 8B | 8B | A | 24 tok/s |
Yes, RTX 4060 Laptop 8GB can run Magistral 7B with a A grade (Runs with offload). Expected decode speed: 44.5 tok/s.
Magistral 7B (7B parameters) requires approximately 7.9 GB of memory with Q4_K_M quantization.
The recommended quantization for Magistral 7B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4060 Laptop 8GB, Magistral 7B achieves approximately 44.5 tokens per second decode speed with a time-to-first-token of 4353ms using Q4_K_M quantization.
For coding workloads, Magistral 7B on RTX 4060 Laptop 8GB receives a A grade with 44.5 tok/s and 8K context.
On RTX 4060 Laptop 8GB, Magistral 7B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/magistral-7b-on-rtx-4060-laptop-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: