Can Yi Coder 9B run on RX 7700 XT 12GB?

YES — Runs Great

B67Good
Estimated from fit model

Yi Coder 9B needs ~9.1 GB VRAM. RX 7700 XT 12GB has 12.0 GB. With Q4_K_M quantization, expect ~51 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: StandardBottleneck: Balanced
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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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 9.1 GB, 51.3 tok/s, Runs well
9.1 GB required12.0 GB available
76% VRAM used

Fit status

Runs well

Decode

51.3 tok/s

TTFT

3771 ms

Safe context

48K

Memory

9.1 GB / 12.0 GB

Memory breakdown

Weights5.5 GB
KV Cache1.5 GB
Runtime0.9 GB
Headroom1.2 GB

See how fast it feels

See how fast it feelsYi Coder 9B on RX 7700 XT 12GB
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: 51.3 tok/s decode · 3.8s TTFT (warm) · 128 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

WorkloadGradeFitDecodeTTFTContext
ChatBRuns well51.3 tok/s2057 ms48K
CodingBRuns well51.3 tok/s3771 ms48K
Agentic CodingBTight fit51.3 tok/s5485 ms48K
ReasoningBRuns well51.3 tok/s4456 ms48K
RAGBTight fit51.3 tok/s6856 ms48K

Quantization options

How Yi Coder 9B (9B params) fits at each quantization level on RX 7700 XT 12GB (12.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.5 GB
LowB62
Q3_K_S
3
4.4 GB
LowB63
NVFP4
4
5.0 GB
MediumB64
Q4_K_M
4
5.5 GB
MediumB65
Q5_K_M
5
6.5 GB
HighB64
Q6_KBest for your GPU
6
7.4 GB
HighB64
Q8_0
8
9.6 GB
Very HighF0
F16
16
18.5 GB
MaximumF0

Get started

Copy-paste commands to run Yi Coder 9B on your machine.

Run

lms load Yi-Coder-9B-Chat && lms server start

Frequently asked questions

Can RX 7700 XT 12GB run Yi Coder 9B?

Yes, RX 7700 XT 12GB can run Yi Coder 9B with a B grade (Runs well). Expected decode speed: 51.3 tok/s.

How much VRAM does Yi Coder 9B need?

Yi Coder 9B (9B parameters) requires approximately 9.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Yi Coder 9B?

The recommended quantization for Yi Coder 9B is Q4_K_M, which balances quality and memory efficiency.

What speed will Yi Coder 9B run at on RX 7700 XT 12GB?

On RX 7700 XT 12GB, Yi Coder 9B achieves approximately 51.3 tokens per second decode speed with a time-to-first-token of 3771ms using Q4_K_M quantization.

Can RX 7700 XT 12GB run Yi Coder 9B for coding?

For coding workloads, Yi Coder 9B on RX 7700 XT 12GB receives a B grade with 51.3 tok/s and 48K context.

What context window can Yi Coder 9B use on RX 7700 XT 12GB?

On RX 7700 XT 12GB, Yi Coder 9B can safely use up to 48K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for RX 7700 XT 12GBSee all hardware for Yi Coder 9B
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