~$2,499 MSRP
jointpreferences mistral 7b sft helpful needs ~9.2 GB VRAM. Radeon AI PRO R9700 32GB has 32.0 GB. With Q4_K_M quantization, expect ~88 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
88.4 tok/s
TTFT
2189 ms
Safe context
461K
Memory
9.2 GB / 32.0 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 | 88.4 tok/s | 1194 ms | 461K |
| Coding | C | Runs well | 88.4 tok/s | 2189 ms | 461K |
| Agentic Coding | C | Runs well | 88.4 tok/s | 3184 ms | 461K |
| Reasoning | C | Runs well | 88.4 tok/s | 2587 ms | 461K |
| RAG | C | Runs well | 88.4 tok/s | 3981 ms | 461K |
How jointpreferences mistral 7b sft helpful (7B params) fits at each quantization level on Radeon AI PRO R9700 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | C42 |
Q3_K_S | 3 | 3.4 GB | Low | C43 |
NVFP4 | 4 |
Copy-paste commands to run jointpreferences mistral 7b sft helpful on your machine.
Run
lms load hf-richarderkhov--jointpreferences---mistral-7b-sft-helpful-gguf && lms server startUpgrade options
Yes, Radeon AI PRO R9700 32GB can run jointpreferences mistral 7b sft helpful with a C grade (Runs well). Expected decode speed: 88.4 tok/s.
jointpreferences mistral 7b sft helpful (7B parameters) requires approximately 9.2 GB of memory with Q4_K_M quantization.
The recommended quantization for jointpreferences mistral 7b sft helpful is Q4_K_M, which balances quality and memory efficiency.
On Radeon AI PRO R9700 32GB, jointpreferences mistral 7b sft helpful achieves approximately 88.4 tokens per second decode speed with a time-to-first-token of 2189ms using Q4_K_M quantization.
For coding workloads, jointpreferences mistral 7b sft helpful on Radeon AI PRO R9700 32GB receives a C grade with 88.4 tok/s and 461K context.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-richarderkhov--jointpreferences---mistral-7b-sft-helpful-gguf-on-radeon-ai-pro-r9700-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
3.9 GB |
| Medium |
| C43 |
Q4_K_M | 4 | 4.3 GB | Medium | C43 |
Q5_K_M | 5 | 5.0 GB | High | C43 |
Q6_K | 6 | 5.7 GB | High | C43 |
Q8_0 | 8 | 7.5 GB | Very High | C44 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | C47 |
On Radeon AI PRO R9700 32GB, jointpreferences mistral 7b sft helpful can safely use up to 461K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.