Will It Run AI

Can Falcon H1 7B Instruct run on GTX 1080 8GB?

YES — Tight Fit

C51Usable
Estimated from fit model

Falcon H1 7B Instruct needs ~7.1 GB VRAM. GTX 1080 8GB has 8.0 GB. With Q4_K_M quantization, expect ~44 tok/s.

Runtime: OllamaCapacity: TightBandwidth: LowStack: BasicBottleneck: 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) — 7.1 GB, 44.2 tok/s, Tight fit
7.1 GB required8.0 GB available
89% VRAM used

Fit status

Tight fit

Decode

44.2 tok/s

TTFT

4379 ms

Safe context

34K

Memory

7.1 GB / 8.0 GB

Memory breakdown

Weights4.3 GB
KV Cache0.8 GB
Runtime1.2 GB
Headroom0.8 GB

See how fast it feels

See how fast it feelsFalcon H1 7B Instruct on GTX 1080 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: 44.2 tok/s decode · 4.4s TTFT (warm) · 111 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Older PCIe generation

PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatCTight fit44.2 tok/s2388 ms34K
CodingCTight fit44.2 tok/s4379 ms34K
Agentic CodingCRuns with offload44.2 tok/s6369 ms34K
ReasoningCTight fit44.2 tok/s5175 ms34K
RAGCRuns with offload44.2 tok/s7961 ms34K

Quantization options

How Falcon H1 7B Instruct (7B params) fits at each quantization level on GTX 1080 8GB (8.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowC53
Q3_K_S
3
3.4 GB
LowC53
NVFP4
4
3.9 GB
MediumC53
Q4_K_M
4
4.3 GB
MediumC53
Q5_K_MBest for your GPU
5
5.0 GB
HighC53
Q6_K
6
5.7 GB
HighF0
Q8_0
8
7.5 GB
Very HighF0
F16
16
14.3 GB
MaximumF0

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

Upgrade-Optionen

Hardware, die Falcon H1 7B Instruct gut ausführt

NVIDIARTX 3060 12GBGünstige Wahl
12 GB VRAM (+4)360 GB/s (+40)
C
Raises estimated decode speed by about 26%.55.6 tok/s Dekodierung

Raises estimated decode speed by about 26%.

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

ca. $329 MSRP

NVIDIARTX 5070 12GBBestes Preis-Leistungs-Verhältnis
12 GB VRAM (+4)672 GB/s (+352)
B
Raises estimated decode speed by about 122%.98 tok/s Dekodierung

Raises estimated decode speed by about 122%.

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

ca. $549 MSRP

NVIDIARTX 4070 Super 12GBNVIDIA-Upgrade
12 GB VRAM (+4)504 GB/s (+184)
B
Raises estimated decode speed by about 106%.90.9 tok/s Dekodierung

Raises estimated decode speed by about 106%.

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

ca. $599 MSRP

Frequently asked questions

Can GTX 1080 8GB run Falcon H1 7B Instruct?

Yes, GTX 1080 8GB can run Falcon H1 7B Instruct with a C grade (Tight fit). Expected decode speed: 44.2 tok/s.

How much VRAM does Falcon H1 7B Instruct need?

Falcon H1 7B Instruct (7B parameters) requires approximately 7.1 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 GTX 1080 8GB?

On GTX 1080 8GB, Falcon H1 7B Instruct achieves approximately 44.2 tokens per second decode speed with a time-to-first-token of 4379ms using Q4_K_M quantization.

Can GTX 1080 8GB run Falcon H1 7B Instruct for coding?

For coding workloads, Falcon H1 7B Instruct on GTX 1080 8GB receives a C grade with 44.2 tok/s and 34K context.

What context window can Falcon H1 7B Instruct use on GTX 1080 8GB?

On GTX 1080 8GB, Falcon H1 7B Instruct can safely use up to 34K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for GTX 1080 8GBSee all hardware for Falcon H1 7B Instruct
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