Can Falcon H1 7B Instruct run on RX 9060 8GB?

YES — Tight Fit

C51Usable

Estimated from fit model

Falcon H1 7B Instruct needs ~6.8 GB VRAM. RX 9060 8GB has 8.0 GB. With Q4_K_M quantization, expect ~43 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: 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) — 6.8 GB, 42.5 tok/s, Tight fit

6.8 GB required8.0 GB available

85% VRAM used

Fit status

Tight fit

Decode

42.5 tok/s

TTFT

4556 ms

Safe context

40K

Memory

6.8 GB / 8.0 GB

Memory breakdown

Weights4.3 GB

KV Cache0.8 GB

Runtime0.9 GB

Headroom0.8 GB

See how fast it feels

See how fast it feelsFalcon H1 7B Instruct on RX 9060 8GB
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: 42.5 tok/s decode · 4.6s TTFT (warm) · 106 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	C	Runs well	42.5 tok/s	2485 ms	40K
Coding	C	Tight fit	42.5 tok/s	4556 ms	40K
Agentic Coding	C	Runs with offload	42.5 tok/s	6627 ms	40K
Reasoning	C	Tight fit	42.5 tok/s	5385 ms	40K
RAG	C	Runs with offload	42.5 tok/s	8284 ms	40K

Quantization options

How Falcon H1 7B Instruct (7B params) fits at each quantization level on RX 9060 8GB (8.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	2.7 GB	Low	C53
Q3_K_S	3	3.4 GB	Low	C53
NVFP4	4	3.9 GB	Medium	C53
Q4_K_M	4	4.3 GB	Medium	C53
Q5_K_MBest for your GPU	5	5.0 GB	High	C53
Q6_K	6	5.7 GB	High	F0
Q8_0	8	7.5 GB	Very High	F0
F16	16	14.3 GB	Maximum	F0

Get started

Copy-paste commands to run Falcon H1 7B Instruct on your machine.

Run

lms load hf-tiiuae--falcon-h1-7b-instruct-gguf && lms server start

Opções de upgrade

Hardware que roda bem Falcon H1 7B Instruct

RX 7700 XT 12GBOpção econômica

12 GB VRAM (+4)432 GB/s (+144)

Raises estimated decode speed by about 43%.60.7 tok/s decodificação

Raises estimated decode speed by about 43%.

Adds memory headroom for longer context windows and future model growth.

~$449 MSRP

RX 6700 XT 12GBMelhor custo-benefício

12 GB VRAM (+4)384 GB/s (+96)

Adds memory headroom for longer context windows and future model growth.46.8 tok/s decodificação

Adds memory headroom for longer context windows and future model growth.

~$479 MSRP

RX 9070 16GBUpgrade AMD

16 GB VRAM (+8)640 GB/s (+352)

Raises estimated decode speed by about 119%.92.9 tok/s decodificação

Raises estimated decode speed by about 119%.

Adds memory headroom for longer context windows and future model growth.

~$479 MSRP

Frequently asked questions

Can RX 9060 8GB run Falcon H1 7B Instruct?

Yes, RX 9060 8GB can run Falcon H1 7B Instruct with a C grade (Tight fit). Expected decode speed: 42.5 tok/s.

How much VRAM does Falcon H1 7B Instruct need?

Falcon H1 7B Instruct (7B parameters) requires approximately 6.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Falcon H1 7B Instruct?

The recommended quantization for Falcon H1 7B Instruct is Q4_K_M, which balances quality and memory efficiency.

What speed will Falcon H1 7B Instruct run at on RX 9060 8GB?

On RX 9060 8GB, Falcon H1 7B Instruct achieves approximately 42.5 tokens per second decode speed with a time-to-first-token of 4556ms using Q4_K_M quantization.

Can RX 9060 8GB run Falcon H1 7B Instruct for coding?

For coding workloads, Falcon H1 7B Instruct on RX 9060 8GB receives a C grade with 42.5 tok/s and 40K context.

What context window can Falcon H1 7B Instruct use on RX 9060 8GB?

On RX 9060 8GB, Falcon H1 7B Instruct can safely use up to 40K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for RX 9060 8GB See all hardware for Falcon H1 7B Instruct

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