cognitivecomputations Dolphin Mistral 24B Venice Edition needs ~28.3 GB VRAM. RTX PRO 6000 Blackwell Server Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~92 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
91.6 tok/s
TTFT
2113 ms
Safe context
401K
Memory
28.3 GB / 96.0 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 | 91.6 tok/s | 1152 ms | 401K |
| Coding | C | Runs well | 91.6 tok/s | 2113 ms | 401K |
| Agentic Coding | C | Runs well | 91.6 tok/s | 3073 ms | 401K |
| Reasoning | C | Runs well | 91.6 tok/s | 2497 ms | 401K |
| RAG | C | Runs well | 91.6 tok/s | 3841 ms | 401K |
How cognitivecomputations Dolphin Mistral 24B Venice Edition (24B params) fits at each quantization level on RTX PRO 6000 Blackwell Server Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | D39 |
Q3_K_S | 3 | 11.8 GB | Low | D39 |
NVFP4 | 4 | 13.4 GB | Medium | D39 |
Q4_K_M | 4 | 14.6 GB | Medium | D40 |
Q5_K_M | 5 | 17.3 GB | High | D40 |
Q6_K | 6 | 19.7 GB | High | C40 |
Q8_0 | 8 | 25.7 GB | Very High | C41 |
F16Best for your GPU | 16 | 49.2 GB | Maximum | C46 |
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, RTX PRO 6000 Blackwell Server Edition 96GB can run cognitivecomputations Dolphin Mistral 24B Venice Edition with a C grade (Runs well). Expected decode speed: 91.6 tok/s.
cognitivecomputations Dolphin Mistral 24B Venice Edition (24B parameters) requires approximately 28.3 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 RTX PRO 6000 Blackwell Server Edition 96GB, cognitivecomputations Dolphin Mistral 24B Venice Edition achieves approximately 91.6 tokens per second decode speed with a time-to-first-token of 2113ms using Q4_K_M quantization.
For coding workloads, cognitivecomputations Dolphin Mistral 24B Venice Edition on RTX PRO 6000 Blackwell Server Edition 96GB receives a C grade with 91.6 tok/s and 401K context.
On RTX PRO 6000 Blackwell Server Edition 96GB, cognitivecomputations Dolphin Mistral 24B Venice Edition can safely use up to 401K 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.
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Preview: