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URL: https://willitrunai.com/can-run/wizardlm-13b-on-rx-7900m-16gb

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Can WizardLM 13B run on Radeon RX 7900M 16GB?

NO — Won't Fit

F0Won't run
○Estimated from fit model

WizardLM 13B needs ~22.6 GB but Radeon RX 7900M 16GB only has 16.0 GB. Try a smaller quantization or lighter model.

Runtime: llama.cppCapacity: No fitBandwidth: MediumStack: StandardBottleneck: Memory capacity
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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) — 22.6 GB, exceeds 16.0 GB available
22.6 GB required16.0 GB available
141% VRAM needed

6.6 GB over capacity — needs offload or smaller quantization

Fit status

Too heavy

Decode

15.5 tok/s

TTFT

12504 ms

Safe context

7K

Memory

22.6 GB / 16.0 GB

Offload

30%

Memory breakdown

Weights7.9 GB
KV Cache12.2 GB
Runtime0.9 GB
Headroom1.6 GB

See how fast it feels

With memory offload — actual speed may be lower
See how fast it feelsWizardLM 13B on Radeon RX 7900M 16GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 15.5 tok/s decode · 12.5s TTFT (warm) · 39 tok/s prefill

What limits this setup

Usable VRAM is the main blocker for this model.

Not enough usable memory

The model needs 22.6 GB, but this setup only exposes 16.0 GB of usable VRAM.

Best improvement path

Add more VRAM headroom

The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatARuns with offload (needs ~0.3 GB host RAM)30.0 tok/s3520 ms7K
CodingFToo heavy15.5 tok/s12504 ms7K
Agentic CodingFToo heavy6.4 tok/s43807 ms7K
ReasoningFToo heavy15.5 tok/s14778 ms7K
RAGFToo heavy6.4 tok/s54758 ms7K

Quantization options

How WizardLM 13B (13B params) fits at each quantization level on Radeon RX 7900M 16GB (16.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.1 GB
LowB70
Q3_K_S
3
6.4 GB
LowA71
NVFP4
4

Upgrade options

Hardware that runs WizardLM 13B well

RX 7900 XT 20GBBest value
20 GB VRAM (+4)800 GB/s (+224)
B
Makes the model fit on the accelerator instead of staying completely out of reach.33.7 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Raises estimated decode speed by about 117%.

~$899 MSRP

RX 7900 XTX 24GBBudget pick
24 GB VRAM (+8)960 GB/s (+384)
A
Makes the model fit on the accelerator instead of staying completely out of reach.87.2 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$999 MSRP

Radeon AI PRO R9700 32GBAMD upgrade
32 GB VRAM (+16)640 GB/s (+64)
A
Makes the model fit on the accelerator instead of staying completely out of reach.47.6 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$1,899 MSRP

Frequently asked questions

See all results for Radeon RX 7900M 16GBSee all hardware for WizardLM 13B
7.3 GB
Medium
A72
Q4_K_M
4
7.9 GB
MediumA72
Q5_K_M
5
9.4 GB
HighA72
Q6_KBest for your GPU
6
10.7 GB
HighA72
Q8_0
8
13.9 GB
Very HighF0
F16
16
26.7 GB
MaximumF0

Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.