Codestral 22B v0.1 IMat needs ~22.0 GB VRAM. RTX 6000 Ada 48GB has 48.0 GB. With Q4_K_M quantization, expect ~59 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
58.7 tok/s
TTFT
3300 ms
Safe context
177K
Memory
22.0 GB / 48.0 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 | 58.7 tok/s | 1800 ms | 177K |
| Coding | C | Runs well | 58.7 tok/s | 3300 ms | 177K |
| Agentic Coding | C | Runs well | 58.7 tok/s | 4801 ms | 177K |
| Reasoning | C | Runs well | 58.7 tok/s | 3901 ms | 177K |
| RAG | C | Runs well | 58.7 tok/s | 6001 ms | 177K |
How Codestral 22B v0.1 IMat (22B params) fits at each quantization level on RTX 6000 Ada 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 8.6 GB | Low | C42 |
Q3_K_S | 3 | 10.8 GB | Low | C43 |
NVFP4 | 4 |
Copy-paste commands to run Codestral 22B v0.1 IMat on your machine.
Run
lms load hf-legraphista--codestral-22b-v0-1-imat-gguf && lms server startYes, RTX 6000 Ada 48GB can run Codestral 22B v0.1 IMat with a C grade (Runs well). Expected decode speed: 58.7 tok/s.
Codestral 22B v0.1 IMat (22B parameters) requires approximately 22.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Codestral 22B v0.1 IMat is Q4_K_M, which balances quality and memory efficiency.
On RTX 6000 Ada 48GB, Codestral 22B v0.1 IMat achieves approximately 58.7 tokens per second decode speed with a time-to-first-token of 3300ms using Q4_K_M quantization.
For coding workloads, Codestral 22B v0.1 IMat on RTX 6000 Ada 48GB receives a C grade with 58.7 tok/s and 177K context.
On RTX 6000 Ada 48GB, Codestral 22B v0.1 IMat can safely use up to 177K tokens of context. The model's official context limit is —, 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/hf-legraphista--codestral-22b-v0-1-imat-gguf-on-rtx-6000-ada-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
12.3 GB |
| Medium |
| C43 |
Q4_K_M | 4 | 13.4 GB | Medium | C44 |
Q5_K_M | 5 | 15.8 GB | High | C44 |
Q6_K | 6 | 18.0 GB | High | C45 |
Q8_0Best for your GPU | 8 | 23.5 GB | Very High | C47 |
F16 | 16 | 45.1 GB | Maximum | F0 |