InternLM 7B needs ~14.6 GB VRAM. RX 9070 16GB has 16.0 GB. With Q4_K_M quantization, expect ~93 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
Tight fit
Decode
92.9 tok/s
TTFT
2083 ms
Safe context
8K
Memory
14.6 GB / 16.0 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 | A | Runs well | 92.9 tok/s | 1136 ms | 8K |
| Coding | A | Tight fit | 92.9 tok/s | 2083 ms | 8K |
| Agentic Coding | F | Too heavy | 35.8 tok/s | 7869 ms | 8K |
| Reasoning | A | Tight fit | 92.9 tok/s | 2462 ms | 8K |
| RAG | F | Too heavy | 35.8 tok/s | 9836 ms | 8K |
How InternLM 7B (7B params) fits at each quantization level on RX 9070 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 |
Copy-paste commands to run InternLM 7B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "InternLM/InternLM-7B" \
--hf-file "InternLM-7B-Q4_K_M.gguf" \
-c 4096 -ngl 99Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | S | 77.7 tok/s | |
| Qwen 3 14B | 14B | S | 50.2 tok/s | |
| Qwen 3 8B | 8B | S | 87.4 tok/s | |
 Phi-4-reasoning-plus 14B | 14.7B | S | 47.6 tok/s | |
 GPT-OSS 20B | 21B | A | 47.1 tok/s |
Yes, RX 9070 16GB can run InternLM 7B with a A grade (Tight fit). Expected decode speed: 92.9 tok/s.
InternLM 7B (7B parameters) requires approximately 14.6 GB of memory with Q4_K_M quantization.
The recommended quantization for InternLM 7B is Q4_K_M, which balances quality and memory efficiency.
On RX 9070 16GB, InternLM 7B achieves approximately 92.9 tokens per second decode speed with a time-to-first-token of 2083ms using Q4_K_M quantization.
For coding workloads, InternLM 7B on RX 9070 16GB receives a A grade with 92.9 tok/s and 8K context.
On RX 9070 16GB, InternLM 7B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/internlm-7b-on-rx-9070-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: