cognitivecomputations Dolphin Mistral 24B Venice Edition needs ~23.5 GB VRAM. NVIDIA L40S 48GB has 48.0 GB. With Q4_K_M quantization, expect ~46 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
46.0 tok/s
TTFT
4206 ms
Safe context
156K
Memory
23.5 GB / 48.0 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 | 46.0 tok/s | 2294 ms | 156K |
| Coding | C | Runs well | 46.0 tok/s | 4206 ms | 156K |
| Agentic Coding | C | Runs well | 46.0 tok/s | 6117 ms | 156K |
| Reasoning | C | Runs well | 46.0 tok/s | 4970 ms | 156K |
| RAG | C | Runs well | 46.0 tok/s | 7647 ms | 156K |
How cognitivecomputations Dolphin Mistral 24B Venice Edition (24B params) fits at each quantization level on NVIDIA L40S 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | C42 |
Q3_K_S | 3 | 11.8 GB | Low | C43 |
NVFP4 | 4 | 13.4 GB | Medium | C44 |
Q4_K_M | 4 | 14.6 GB | Medium | C44 |
Q5_K_M | 5 | 17.3 GB | High | C45 |
Q6_K | 6 | 19.7 GB | High | C46 |
Q8_0Best for your GPU | 8 | 25.7 GB | Very High | C48 |
F16 | 16 | 49.2 GB | Maximum | F0 |
Copy-paste commands to run cognitivecomputations Dolphin Mistral 24B Venice Edition on your machine.
Run
lms load hf-yixman--cognitivecomputations-dolphin-mistral-24b-venice-edition-gguf && lms server startYes, NVIDIA L40S 48GB can run cognitivecomputations Dolphin Mistral 24B Venice Edition with a C grade (Runs well). Expected decode speed: 46.0 tok/s.
cognitivecomputations Dolphin Mistral 24B Venice Edition (24B parameters) requires approximately 23.5 GB of memory with Q4_K_M quantization.
The recommended quantization for cognitivecomputations Dolphin Mistral 24B Venice Edition is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA L40S 48GB, cognitivecomputations Dolphin Mistral 24B Venice Edition achieves approximately 46.0 tokens per second decode speed with a time-to-first-token of 4206ms using Q4_K_M quantization.
For coding workloads, cognitivecomputations Dolphin Mistral 24B Venice Edition on NVIDIA L40S 48GB receives a C grade with 46.0 tok/s and 156K context.
On NVIDIA L40S 48GB, cognitivecomputations Dolphin Mistral 24B Venice Edition can safely use up to 156K 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-yixman--cognitivecomputations-dolphin-mistral-24b-venice-edition-gguf-on-l40s-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: