Can GLM-4 9B run on RX 6750 XT 12GB?

YES — Runs Great

A76Great

Estimated from fit model

GLM-4 9B needs ~8.2 GB VRAM. RX 6750 XT 12GB has 12.0 GB. With Q4_K_M quantization, expect ~46 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: 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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 8.2 GB, 45.6 tok/s, Runs well

8.2 GB required12.0 GB available

68% VRAM used

Fit status

Runs well

Decode

45.6 tok/s

TTFT

4244 ms

Safe context

116K

Memory

8.2 GB / 12.0 GB

Memory breakdown

Weights5.5 GB

KV Cache0.6 GB

Runtime0.9 GB

Headroom1.2 GB

See how fast it feels

See how fast it feelsGLM-4 9B on RX 6750 XT 12GB
1st promptCold start — includes initialization
>What is local AI inference?
Local AI inference means running an AI language model directly on your own hardware — your laptop, desktop, or server — instead of sending requests to a remote cloud API.

When you run inference locally the model weights are loaded into your GPU or unified memory. Each token you generate requires reading those weights from memory, so memory bandwidth is the main bottleneck for decode speed.

Key benefits of running locally:
  - Full privacy: your prompts never leave your machine
  - No per-token cost or rate limits
  - Works offline once the model is downloaded
  - Latency depends only on your hardware
2nd promptWarm — model ready, no init overhead
>How much VRAM do I need?
It depends on the model size and quantization level. A rough rule of thumb:

  Model size     Q4 (4-bit)    Q8 (8-bit)    FP16
  7B params      ~4.3 GB       ~7.5 GB       ~14 GB
  13B params     ~7.9 GB       ~13.9 GB      ~26 GB
  70B params     ~42.7 GB      ~74.9 GB      ~140 GB

Most people use 4-bit quantization (Q4_K_M) which gives 90-95% of full quality at a fraction of the memory. A 24 GB GPU can comfortably run most 7B-13B models.
Estimated: 45.6 tok/s decode · 4.2s TTFT (warm) · 114 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	A	Runs well	45.6 tok/s	2315 ms	116K
Coding	A	Runs well	45.6 tok/s	4244 ms	116K
Agentic Coding	A	Runs well	45.6 tok/s	6173 ms	116K
Reasoning	A	Runs well	45.6 tok/s	5016 ms	116K
RAG	A	Runs well	45.6 tok/s	7717 ms	116K

Quantization options

How GLM-4 9B (9B params) fits at each quantization level on RX 6750 XT 12GB (12.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.5 GB	Low	A71
Q3_K_S	3	4.4 GB	Low	A73
NVFP4	4	5.0 GB	Medium	A73
Q4_K_M	4	5.5 GB	Medium	A74
Q5_K_M	5	6.5 GB	High	A74
Q6_KBest for your GPU	6	7.4 GB	High	A73
Q8_0	8	9.6 GB	Very High	F0
F16	16	18.5 GB	Maximum	F0

Get started

Copy-paste commands to run GLM-4 9B on your machine.

Run

ollama run glm4

Your hardware

More models your RX 6750 XT 12GB can run

Model	Params	Grade	Decode
Qwen 3 14B	14B	A	18.1 tok/s
Phi-4-reasoning-plus 14B	14.7B	A	14.6 tok/s
Ministral 3 14B	14B	A	18 tok/s
Phi-4 14B	14B	A	16.4 tok/s
Qwen 2.5 14B	14B	B	16.8 tok/s

Frequently asked questions

Can RX 6750 XT 12GB run GLM-4 9B?

Yes, RX 6750 XT 12GB can run GLM-4 9B with a A grade (Runs well). Expected decode speed: 45.6 tok/s.

How much VRAM does GLM-4 9B need?

GLM-4 9B (9B parameters) requires approximately 8.2 GB of memory with Q4_K_M quantization.

What is the best quantization for GLM-4 9B?

The recommended quantization for GLM-4 9B is Q4_K_M, which balances quality and memory efficiency.

What speed will GLM-4 9B run at on RX 6750 XT 12GB?

On RX 6750 XT 12GB, GLM-4 9B achieves approximately 45.6 tokens per second decode speed with a time-to-first-token of 4244ms using Q4_K_M quantization.

Can RX 6750 XT 12GB run GLM-4 9B for coding?

For coding workloads, GLM-4 9B on RX 6750 XT 12GB receives a A grade with 45.6 tok/s and 116K context.

What context window can GLM-4 9B use on RX 6750 XT 12GB?

On RX 6750 XT 12GB, GLM-4 9B can safely use up to 116K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

See all results for RX 6750 XT 12GB See all hardware for GLM-4 9B

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<iframe src="https://willitrunai.com/embed/glm-4-9b-on-rx-6750-xt-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

45.6 tok/s

2315 ms

116K

Coding

Runs well

45.6 tok/s

4244 ms

116K

Agentic Coding

Runs well

45.6 tok/s

6173 ms

116K

Reasoning

Runs well

45.6 tok/s

5016 ms

116K

RAG

Runs well

45.6 tok/s

7717 ms

116K

Quant

Bits

VRAM

Quality

Fit

Q2_K

3.5 GB

Low

A71

Q3_K_S

4.4 GB

Low

A73

NVFP4

5.0 GB

Medium

A73

Q4_K_M

5.5 GB

Medium

A74

Q5_K_M

6.5 GB

High

A74

Q6_KBest for your GPU

7.4 GB

High

A73

Q8_0

9.6 GB

Very High

F16

18.5 GB

Maximum

Model

Params

Grade

Decode

Capabilities

Qwen 3 14B

14B

18.1 tok/s

Phi-4-reasoning-plus 14B

14.7B

14.6 tok/s

Ministral 3 14B

14B

18 tok/s

Phi-4 14B

14B

16.4 tok/s

Qwen 2.5 14B

14B

16.8 tok/s

Frequently asked questions

Can RX 6750 XT 12GB run GLM-4 9B?

Yes, RX 6750 XT 12GB can run GLM-4 9B with a A grade (Runs well). Expected decode speed: 45.6 tok/s.

How much VRAM does GLM-4 9B need?

GLM-4 9B (9B parameters) requires approximately 8.2 GB of memory with Q4_K_M quantization.

What is the best quantization for GLM-4 9B?

The recommended quantization for GLM-4 9B is Q4_K_M, which balances quality and memory efficiency.

What speed will GLM-4 9B run at on RX 6750 XT 12GB?

On RX 6750 XT 12GB, GLM-4 9B achieves approximately 45.6 tokens per second decode speed with a time-to-first-token of 4244ms using Q4_K_M quantization.

Can RX 6750 XT 12GB run GLM-4 9B for coding?

For coding workloads, GLM-4 9B on RX 6750 XT 12GB receives a A grade with 45.6 tok/s and 116K context.

What context window can GLM-4 9B use on RX 6750 XT 12GB?

On RX 6750 XT 12GB, GLM-4 9B can safely use up to 116K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.