Can Solar 7B run on Radeon RX 7900M 16GB?
YES — Runs Great
Solar 7B needs ~9.7 GB VRAM. Radeon RX 7900M 16GB has 16.0 GB. With Q4_K_M quantization, expect ~86 tok/s.
Operating mode
Choose the run profile you care about
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
85.6 tok/s
TTFT
2263 ms
Safe context
8K
Memory
9.7 GB / 16.0 GB
Memory breakdown
See how fast it feels
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 85.6 tok/s | 1234 ms | 8K |
| Coding | A | Runs well | 85.6 tok/s | 2263 ms | 8K |
| Agentic Coding | A | Runs well | 85.6 tok/s | 3291 ms | 8K |
| Reasoning | A | Runs well | 85.6 tok/s | 2674 ms | 8K |
| RAG | A | Runs well | 85.6 tok/s | 4114 ms | 8K |
Quantization options
How Solar 7B (7B params) fits at each quantization level on Radeon RX 7900M 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B67 |
Q3_K_S | 3 | 3.4 GB | Low | B68 |
NVFP4 | 4 | 3.9 GB | Medium | B68 |
Q4_K_M | 4 | 4.3 GB | Medium | B69 |
Q5_K_M | 5 | 5.0 GB | High | B69 |
Q6_K | 6 | 5.7 GB | High | A70 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | A72 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Get started
Copy-paste commands to run Solar 7B on your machine.
Run
lms load Solar-7B && lms server startYour hardware
More models your Radeon RX 7900M 16GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 👁 Alibaba Qwen 3.5 9B | 9B | S | 66.5 tok/s | |
| 👁 Alibaba Qwen 3 14B | 14B | S | 43 tok/s | |
| 👁 Alibaba Qwen 3 8B | 8B | S | 74.9 tok/s | |
| 👁 Microsoft Phi-4-reasoning-plus 14B | 14.7B | S | 40.7 tok/s | |
| 👁 OpenAI GPT-OSS 20B | 21B | A | 39.3 tok/s |
