MacBook Pro M4 Max 48GBOpción económica
48 GB Unified (+16)546 GB/s (+34)
B
Sube la velocidad estimada de decodificación alrededor de un 63%.37.4 tok/s decodificación
Sube la velocidad estimada de decodificación alrededor de un 63%.
~$2,499 MSRP
Can Codestral 22B run on Radeon Pro W6800 32GB?
YES — Runs Great
B61Good
Estimated from fit model
Codestral 22B needs ~20.0 GB VRAM. Radeon Pro W6800 32GB has 32.0 GB. With Q4_K_M quantization, expect ~21 tok/s.
Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: StandardBottleneck: Balanced
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
Q4_K_M (Medium quality) — 20.0 GB, 23.0 tok/s, Runs well
20.0 GB required32.0 GB available
63% VRAM used
Fit status
Runs well
Decode
23.0 tok/s
TTFT
8429 ms
Safe context
33K
Memory
20.0 GB / 32.0 GB
Memory breakdown
Weights13.4 GB
KV Cache2.4 GB
Runtime0.9 GB
Headroom3.2 GB
See how fast it feels
See how fast it feelsCodestral 22B on Radeon Pro W6800 32GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort:
def quicksort(arr):
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quicksort(left) + middle + quicksort(right)
# Example usage
numbers = [3, 6, 8, 10, 1, 2, 1]
print(quicksort(numbers)) # [1, 1, 2, 3, 6, 8, 10]
The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]:
"""Sort a list using the quicksort algorithm.
Args:
arr: List of integers to sort.
Returns:
A new sorted list.
"""
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quicksort(left) + middle + quicksort(right)
Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 23.0 tok/s decode · 8.4s TTFT (warm) · 57 tok/s prefill
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 | B | Runs well | 21.4 tok/s | 4943 ms | 33K |
| Coding | B | Runs well | 21.4 tok/s | 9061 ms | 33K |
| Agentic Coding | B | Runs well | 21.4 tok/s | 13180 ms | 33K |
| Reasoning | B | Runs well | 21.4 tok/s | 10709 ms | 33K |
| RAG | B | Runs well | 21.4 tok/s | 16475 ms | 33K |
Quantization options
How Codestral 22B (22B params) fits at each quantization level on Radeon Pro W6800 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 8.6 GB | Low | B55 |
Q3_K_S | 3 | 10.8 GB | Low | B56 |
NVFP4 | 4 | 12.3 GB | Medium | B57 |
Q4_K_M | 4 | 13.4 GB | Medium | B58 |
Q5_K_M | 5 | 15.8 GB | High | B59 |
Q6_K | 6 | 18.0 GB | High | B59 |
Q8_0Best for your GPU | 8 | 23.5 GB | Very High | B59 |
F16 | 16 | 45.1 GB | Maximum | F0 |
Get started
Copy-paste commands to run Codestral 22B on your machine.
Run
ollama run codestralOpciones de mejora
Hardware que ejecuta bien Codestral 22B
Frequently asked questions
Can Radeon Pro W6800 32GB run Codestral 22B?
Yes, Radeon Pro W6800 32GB can run Codestral 22B with a B grade (Runs well). Expected decode speed: 21.4 tok/s.
How much VRAM does Codestral 22B need?
Codestral 22B (22B parameters) requires approximately 20.0 GB of memory with Q4_K_M quantization.
What is the best quantization for Codestral 22B?
The recommended quantization for Codestral 22B is Q4_K_M, which balances quality and memory efficiency.
What speed will Codestral 22B run at on Radeon Pro W6800 32GB?
On Radeon Pro W6800 32GB, Codestral 22B achieves approximately 21.4 tokens per second decode speed with a time-to-first-token of 9061ms using Q4_K_M quantization.
Can Radeon Pro W6800 32GB run Codestral 22B for coding?
For coding workloads, Codestral 22B on Radeon Pro W6800 32GB receives a B grade with 21.4 tok/s and 33K context.
What context window can Codestral 22B use on Radeon Pro W6800 32GB?
On Radeon Pro W6800 32GB, Codestral 22B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.
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