InternLM Chat 7B needs ~16.2 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
8K
Memory
16.2 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 | A | Runs well | 88.4 tok/s | 1194 ms | 8K |
| Coding | A | Runs well | 88.4 tok/s | 2189 ms | 8K |
| Agentic Coding | A | Runs well | 88.4 tok/s | 3184 ms | 8K |
| Reasoning | A | Runs well | 88.4 tok/s | 2587 ms | 8K |
| RAG | A | Runs well | 88.4 tok/s | 3981 ms | 8K |
How InternLM Chat 7B (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 | B64 |
Q3_K_S | 3 | 3.4 GB | Low | B64 |
NVFP4 | 4 |
Copy-paste commands to run InternLM Chat 7B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "InternLM/InternLM-Chat-7B" \
--hf-file "InternLM-Chat-7B-Q4_K_M.gguf" \
-c 4096 -ngl 99Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 57.1 tok/s | |
| Qwen 3.5 27B | 27B | S | 24.8 tok/s |
Yes, Radeon AI PRO R9700 32GB can run InternLM Chat 7B with a A grade (Runs well). Expected decode speed: 88.4 tok/s.
InternLM Chat 7B (7B parameters) requires approximately 16.2 GB of memory with Q4_K_M quantization.
The recommended quantization for InternLM Chat 7B is Q4_K_M, which balances quality and memory efficiency.
On Radeon AI PRO R9700 32GB, InternLM Chat 7B 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, InternLM Chat 7B on Radeon AI PRO R9700 32GB receives a A grade with 88.4 tok/s and 8K context.
On Radeon AI PRO R9700 32GB, InternLM Chat 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-chat-7b-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 |
| B64 |
Q4_K_M | 4 | 4.3 GB | Medium | B64 |
Q5_K_M | 5 | 5.0 GB | High | B64 |
Q6_K | 6 | 5.7 GB | High | B65 |
Q8_0 | 8 | 7.5 GB | Very High | B65 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | B68 |
| Qwen 3.6 27B | 27B | S | 18.8 tok/s |
| Qwen 3.6 35B A3B | 35B | S | 48 tok/s |
| Qwen3-VL 30B A3B Instruct | 30B | S | 59.1 tok/s |