Will It Run AI

Can GLM-4 9B run on Radeon RX 6850M XT 12GB?

YES — Runs Great

A76Great
Estimated from fit model

GLM-4 9B needs ~8.2 GB VRAM. Radeon RX 6850M XT 12GB has 12.0 GB. With Q4_K_M quantization, expect ~44 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) 8.2 GB, 48.2 tok/s, Runs well
8.2 GB required12.0 GB available
68% VRAM used

Fit status

Runs well

Decode

48.2 tok/s

TTFT

4017 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 Radeon RX 6850M 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: 48.2 tok/s decode · 4.0s TTFT (warm) · 121 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
ChatARuns well48.2 tok/s2191 ms116K
CodingARuns well44.1 tok/s4393 ms116K
Agentic CodingARuns well48.2 tok/s5843 ms116K
ReasoningARuns well48.2 tok/s4747 ms116K
RAGARuns well48.2 tok/s7303 ms116K

Quantization options

How GLM-4 9B (9B params) fits at each quantization level on Radeon RX 6850M XT 12GB (12.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.5 GB
LowA71
Q3_K_S
3
4.4 GB
LowA73
NVFP4
4
5.0 GB
MediumA73
Q4_K_M
4
5.5 GB
MediumA74
Q5_K_M
5
6.5 GB
HighA74
Q6_KBest for your GPU
6
7.4 GB
HighA73
Q8_0
8
9.6 GB
Very HighF0
F16
16
18.5 GB
MaximumF0

Get started

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

Run

ollama run glm4

Your hardware

More models your Radeon RX 6850M XT 12GB can run

ModelParamsGradeDecodeCapabilities
AlibabaQwen 3 14B14BA19.1 tok/s
MicrosoftPhi-4-reasoning-plus 14B14.7BA15.4 tok/s
MistralMinistral 3 14B14BA19 tok/s
MicrosoftPhi-4 14B14BA17.3 tok/s
AlibabaQwen 2.5 14B14BB17.7 tok/s

Frequently asked questions

Can Radeon RX 6850M XT 12GB run GLM-4 9B?

Yes, Radeon RX 6850M XT 12GB can run GLM-4 9B with a A grade (Runs well). Expected decode speed: 44.1 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 Radeon RX 6850M XT 12GB?

On Radeon RX 6850M XT 12GB, GLM-4 9B achieves approximately 44.1 tokens per second decode speed with a time-to-first-token of 4393ms using Q4_K_M quantization.

Can Radeon RX 6850M XT 12GB run GLM-4 9B for coding?

For coding workloads, GLM-4 9B on Radeon RX 6850M XT 12GB receives a A grade with 44.1 tok/s and 116K context.

What context window can GLM-4 9B use on Radeon RX 6850M XT 12GB?

On Radeon RX 6850M 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 Radeon RX 6850M XT 12GBSee all hardware for GLM-4 9B
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