Gemma 4 E2B needs ~5.6 GB VRAM. RTX 2000 Ada Laptop 8GB has 8.0 GB. With Q4_K_M quantization, expect ~60 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
65.3 tok/s
TTFT
2964 ms
Safe context
87K
Memory
5.6 GB / 8.0 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 | A | Runs well | 60.1 tok/s | 1758 ms | 87K |
| Coding | A | Runs well | 60.1 tok/s | 3223 ms | 87K |
| Agentic Coding | A | Runs well | 60.1 tok/s | 4688 ms | 87K |
| Reasoning | A | Runs well | 60.1 tok/s | 3809 ms | 87K |
| RAG | A | Runs well | 60.1 tok/s | 5860 ms | 87K |
How Gemma 4 E2B (5.099999904632568B params) fits at each quantization level on RTX 2000 Ada Laptop 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.0 GB | Low | A75 |
Q3_K_S | 3 | 2.5 GB | Low | A76 |
NVFP4 | 4 |
Copy-paste commands to run Gemma 4 E2B on your machine.
Run
ollama run gemma4:e2bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 8B | A | 23.7 tok/s | ||
| 8B | A | 25.1 tok/s |
Yes, RTX 2000 Ada Laptop 8GB can run Gemma 4 E2B with a A grade (Runs well). Expected decode speed: 60.1 tok/s.
Gemma 4 E2B (5.099999904632568B parameters) requires approximately 5.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemma 4 E2B is Q4_K_M, which balances quality and memory efficiency.
On RTX 2000 Ada Laptop 8GB, Gemma 4 E2B achieves approximately 60.1 tokens per second decode speed with a time-to-first-token of 3223ms using Q4_K_M quantization.
For coding workloads, Gemma 4 E2B on RTX 2000 Ada Laptop 8GB receives a A grade with 60.1 tok/s and 87K context.
On RTX 2000 Ada Laptop 8GB, Gemma 4 E2B can safely use up to 87K tokens of context. The model's official context limit is 128K, 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/gemma-4-e2b-on-rtx-2000-ada-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:
2.9 GB |
| Medium |
| A76 |
Q4_K_M | 4 | 3.1 GB | Medium | A77 |
Q5_K_M | 5 | 3.7 GB | High | A76 |
Q6_KBest for your GPU | 6 | 4.2 GB | High | A76 |
Q8_0 | 8 | 5.5 GB | Very High | F0 |
F16 | 16 | 10.5 GB | Maximum | F0 |
| 8B | A | 25.1 tok/s |
| 8B | A | 23.7 tok/s |
| 8B | A | 25.1 tok/s |