cognitivecomputations Dolphin3.0 R1 Mistral 24B needs ~23.5 GB VRAM. RTX PRO 5000 Blackwell 48GB has 48.0 GB. With Q4_K_M quantization, expect ~77 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
77.1 tok/s
TTFT
2511 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 | 77.1 tok/s | 1369 ms | 156K |
| Coding | C | Runs well | 77.1 tok/s | 2511 ms | 156K |
| Agentic Coding | C | Runs well | 77.1 tok/s | 3652 ms | 156K |
| Reasoning | C | Runs well | 77.1 tok/s | 2967 ms | 156K |
| RAG | C | Runs well | 77.1 tok/s | 4565 ms | 156K |
How cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B params) fits at each quantization level on RTX PRO 5000 Blackwell 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | C43 |
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 Dolphin3.0 R1 Mistral 24B on your machine.
Run
lms load hf-bartowski--cognitivecomputations-dolphin3-0-r1-mistral-24b-gguf && lms server startYes, RTX PRO 5000 Blackwell 48GB can run cognitivecomputations Dolphin3.0 R1 Mistral 24B with a C grade (Runs well). Expected decode speed: 77.1 tok/s.
cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B parameters) requires approximately 23.5 GB of memory with Q4_K_M quantization.
The recommended quantization for cognitivecomputations Dolphin3.0 R1 Mistral 24B is Q4_K_M, which balances quality and memory efficiency.
On RTX PRO 5000 Blackwell 48GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B achieves approximately 77.1 tokens per second decode speed with a time-to-first-token of 2511ms using Q4_K_M quantization.
For coding workloads, cognitivecomputations Dolphin3.0 R1 Mistral 24B on RTX PRO 5000 Blackwell 48GB receives a C grade with 77.1 tok/s and 156K context.
On RTX PRO 5000 Blackwell 48GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B 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-bartowski--cognitivecomputations-dolphin3-0-r1-mistral-24b-gguf-on-rtx-pro-5000-blackwell-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: