cognitivecomputations Dolphin3.0 R1 Mistral 24B needs ~47.2 GB VRAM. AMD Instinct MI350X 288GB has 288.0 GB. With Q4_K_M quantization, expect ~336 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
336.0 tok/s
TTFT
576 ms
Safe context
1.4M
Memory
47.2 GB / 288.0 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 | 336.0 tok/s | 350 ms | 1.4M |
| Coding | C | Runs well | 336.0 tok/s | 576 ms | 1.4M |
| Agentic Coding | C | Runs well | 336.0 tok/s | 838 ms | 1.4M |
| Reasoning | C | Runs well | 336.0 tok/s | 681 ms | 1.4M |
| RAG | C | Runs well | 336.0 tok/s | 1048 ms | 1.4M |
How cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B params) fits at each quantization level on AMD Instinct MI350X 288GB (288.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | D36 |
Q3_K_S | 3 | 11.8 GB | Low | D36 |
NVFP4 | 4 |
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, AMD Instinct MI350X 288GB can run cognitivecomputations Dolphin3.0 R1 Mistral 24B with a C grade (Runs well). Expected decode speed: 336.0 tok/s.
cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B parameters) requires approximately 47.2 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 AMD Instinct MI350X 288GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B achieves approximately 336.0 tokens per second decode speed with a time-to-first-token of 576ms using Q4_K_M quantization.
For coding workloads, cognitivecomputations Dolphin3.0 R1 Mistral 24B on AMD Instinct MI350X 288GB receives a C grade with 336.0 tok/s and 1.4M context.
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-instinct-mi350x-288gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
13.4 GB |
| Medium |
| D36 |
Q4_K_M | 4 | 14.6 GB | Medium | D36 |
Q5_K_M | 5 | 17.3 GB | High | D36 |
Q6_K | 6 | 19.7 GB | High | D37 |
Q8_0 | 8 | 25.7 GB | Very High | D37 |
F16Best for your GPU | 16 | 49.2 GB | Maximum | D39 |
On AMD Instinct MI350X 288GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B can safely use up to 1.4M tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.