Gemmasutra Mini 2B v1 needs ~3.5 GB VRAM. RTX 2070 Super 8GB has 8.0 GB. With Q4_K_M quantization, expect ~28 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
28.0 tok/s
TTFT
6914 ms
Safe context
326K
Memory
3.5 GB / 8.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 28.0 tok/s | 3771 ms | 326K |
| Coding | C | Runs well | 28.0 tok/s | 6914 ms | 326K |
| Agentic Coding | C | Runs well | 28.0 tok/s | 10057 ms | 326K |
| Reasoning | C | Runs well | 28.0 tok/s | 8171 ms | 326K |
| RAG | C | Runs well | 28.0 tok/s | 12571 ms | 326K |
How Gemmasutra Mini 2B v1 (2B params) fits at each quantization level on RTX 2070 Super 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.8 GB | Low | C50 |
Q3_K_S | 3 | 1.0 GB | Low | C50 |
NVFP4 | 4 | 1.1 GB | Medium | C50 |
Q4_K_M | 4 | 1.2 GB | Medium | C50 |
Q5_K_M | 5 | 1.4 GB | High | C51 |
Q6_K | 6 | 1.6 GB | High | C51 |
Q8_0 | 8 | 2.1 GB | Very High | C52 |
F16Best for your GPU | 16 | 4.1 GB | Maximum | C53 |
Copy-paste commands to run Gemmasutra Mini 2B v1 on your machine.
Run
lms load hf-thedrummer--gemmasutra-mini-2b-v1-gguf && lms server startYes, RTX 2070 Super 8GB can run Gemmasutra Mini 2B v1 with a C grade (Runs well). Expected decode speed: 28.0 tok/s.
Gemmasutra Mini 2B v1 (2B parameters) requires approximately 3.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Gemmasutra Mini 2B v1 is Q4_K_M, which balances quality and memory efficiency.
On RTX 2070 Super 8GB, Gemmasutra Mini 2B v1 achieves approximately 28.0 tokens per second decode speed with a time-to-first-token of 6914ms using Q4_K_M quantization.
For coding workloads, Gemmasutra Mini 2B v1 on RTX 2070 Super 8GB receives a C grade with 28.0 tok/s and 326K context.
On RTX 2070 Super 8GB, Gemmasutra Mini 2B v1 can safely use up to 326K 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-thedrummer--gemmasutra-mini-2b-v1-gguf-on-rtx-2070-super-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: