CodeGeeX 4 9B needs ~8.5 GB VRAM. RTX A2000 12GB has 12.0 GB. With Q4_K_M quantization, expect ~41 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
44.8 tok/s
TTFT
4326 ms
Safe context
108K
Memory
8.5 GB / 12.0 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 | 40.9 tok/s | 2581 ms | 108K |
| Coding | A | Runs well | 40.9 tok/s | 4731 ms | 108K |
| Agentic Coding | A | Runs well | 40.9 tok/s | 6882 ms | 108K |
| Reasoning | A | Runs well | 40.9 tok/s | 5592 ms | 108K |
| RAG | A | Runs well | 40.9 tok/s | 8603 ms | 108K |
How CodeGeeX 4 9B (9B params) fits at each quantization level on RTX A2000 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | A78 |
Q3_K_S | 3 | 4.4 GB | Low | A79 |
NVFP4 | 4 |
Copy-paste commands to run CodeGeeX 4 9B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "THUDM/codegeex4-all-9b" \
--hf-file "codegeex4-all-9b-Q4_K_M.gguf" \
-c 4096 -ngl 99Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 14B | A | 16.9 tok/s | ||
| 14B | A | 16.9 tok/s |
Yes, RTX A2000 12GB can run CodeGeeX 4 9B with a A grade (Runs well). Expected decode speed: 40.9 tok/s.
CodeGeeX 4 9B (9B parameters) requires approximately 8.5 GB of memory with Q4_K_M quantization.
The recommended quantization for CodeGeeX 4 9B is Q4_K_M, which balances quality and memory efficiency.
On RTX A2000 12GB, CodeGeeX 4 9B achieves approximately 40.9 tokens per second decode speed with a time-to-first-token of 4731ms using Q4_K_M quantization.
For coding workloads, CodeGeeX 4 9B on RTX A2000 12GB receives a A grade with 40.9 tok/s and 108K context.
On RTX A2000 12GB, CodeGeeX 4 9B can safely use up to 108K tokens of context. The model's official context limit is 131K, 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/codegeex-4-9b-on-a2000-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
5.0 GB |
| Medium |
| A80 |
Q4_K_M | 4 | 5.5 GB | Medium | A80 |
Q5_K_M | 5 | 6.5 GB | High | A80 |
Q6_KBest for your GPU | 6 | 7.4 GB | High | A80 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |
| 14B | B | 15.4 tok/s |
| 14B | B | 15.7 tok/s |