Ministral 3 8B needs ~10.0 GB VRAM. RTX 2080 Ti 11GB has 11.0 GB. With Q4_K_M quantization, expect ~88 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
Tight fit
Decode
88.2 tok/s
TTFT
2195 ms
Safe context
23K
Memory
10.0 GB / 11.0 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 | S | Runs well | 88.2 tok/s | 1197 ms | 23K |
| Coding | A | Tight fit | 88.2 tok/s | 2195 ms | 23K |
| Agentic Coding | A | Very compromised (needs ~0.5 GB host RAM) | 51.5 tok/s | 5469 ms | 23K |
| Reasoning | A | Tight fit | 88.2 tok/s | 2594 ms | 23K |
| RAG | A | Very compromised | 47.9 tok/s | 7349 ms | 23K |
How Ministral 3 8B (8B params) fits at each quantization level on RTX 2080 Ti 11GB (11.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | A81 |
Q3_K_S | 3 | 3.9 GB | Low | A82 |
NVFP4 | 4 |
Copy-paste commands to run Ministral 3 8B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "mistralai/Ministral-3-8B-Instruct-2512" \
--hf-file "Ministral-3-8B-Instruct-2512-Q4_K_M.gguf" \
-c 4096 -ngl 99Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 9B | S | 78.4 tok/s |
Yes, RTX 2080 Ti 11GB can run Ministral 3 8B with a A grade (Tight fit). Expected decode speed: 88.2 tok/s.
Ministral 3 8B (8B parameters) requires approximately 10.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Ministral 3 8B is Q4_K_M, which balances quality and memory efficiency.
On RTX 2080 Ti 11GB, Ministral 3 8B achieves approximately 88.2 tokens per second decode speed with a time-to-first-token of 2195ms using Q4_K_M quantization.
For coding workloads, Ministral 3 8B on RTX 2080 Ti 11GB receives a A grade with 88.2 tok/s and 23K context.
On RTX 2080 Ti 11GB, Ministral 3 8B can safely use up to 23K tokens of context. The model's official context limit is 262K, 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/ministral-3-8b-on-rtx-2080-ti-11gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
4.5 GB |
| Medium |
| A83 |
Q4_K_M | 4 | 4.9 GB | Medium | A83 |
Q5_K_M | 5 | 5.8 GB | High | A83 |
Q6_KBest for your GPU | 6 | 6.6 GB | High | A83 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |