cognitivecomputations Dolphin3.0 R1 Mistral 24B needs ~31.2 GB VRAM. AMD Instinct MI300A 128GB has 128.0 GB. With Q4_K_M quantization, expect ~253 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
253.4 tok/s
TTFT
764 ms
Safe context
567K
Memory
31.2 GB / 128.0 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 | 253.4 tok/s | 417 ms | 567K |
| Coding | C | Runs well | 253.4 tok/s | 764 ms | 567K |
| Agentic Coding | C | Runs well | 253.4 tok/s | 1111 ms | 567K |
| Reasoning | C | Runs well | 253.4 tok/s | 903 ms | 567K |
| RAG | C | Runs well | 253.4 tok/s | 1389 ms | 567K |
How cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B params) fits at each quantization level on AMD Instinct MI300A 128GB (128.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 9.4 GB | Low | D38 |
Q3_K_S | 3 | 11.8 GB | Low | D38 |
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 MI300A 128GB can run cognitivecomputations Dolphin3.0 R1 Mistral 24B with a C grade (Runs well). Expected decode speed: 253.4 tok/s.
cognitivecomputations Dolphin3.0 R1 Mistral 24B (24B parameters) requires approximately 31.2 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 MI300A 128GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B achieves approximately 253.4 tokens per second decode speed with a time-to-first-token of 764ms using Q4_K_M quantization.
For coding workloads, cognitivecomputations Dolphin3.0 R1 Mistral 24B on AMD Instinct MI300A 128GB receives a C grade with 253.4 tok/s and 567K 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-mi300a-128gb" 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 |
| D39 |
Q4_K_M | 4 | 14.6 GB | Medium | D39 |
Q5_K_M | 5 | 17.3 GB | High | D39 |
Q6_K | 6 | 19.7 GB | High | D39 |
Q8_0 | 8 | 25.7 GB | Very High | D40 |
F16Best for your GPU | 16 | 49.2 GB | Maximum | C44 |
On AMD Instinct MI300A 128GB, cognitivecomputations Dolphin3.0 R1 Mistral 24B can safely use up to 567K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.