FitMyLLM
TII/Dense

TIIFalcon-H1 34B

Falcon-H1 with hybrid SSM+attention architecture. Strong math and coding.

chatcodingreasoningmath
34B
Parameters
32K
Context length
9
Benchmarks
14
Quantizations
40K
HF downloads
Architecture
Dense
Released
2025-07-30
Layers
72
KV Heads
4
Head Dim
128
Family
falcon

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
IQ3_XXS3.25
16.0 GB
14.3 + 1.7 KV
low
IQ3_XS3.5
17.1 GB
15.4 + 1.7 KV
low
Q3_K_S3.64
17.6 GB
16.0 + 1.7 KV
low
IQ3_M3.76
18.2 GB
16.5 + 1.7 KV
low
Q3_K_M4
19.2 GB
17.5 + 1.7 KV
low
Q3_K_L4.3
20.5 GB
18.8 + 1.7 KV
moderate
IQ4_XS4.46
21.1 GB
19.4 + 1.7 KV
moderate
Q4_K_S4.67
22.0 GB
20.3 + 1.7 KV
moderate
Q4_K_M4.89
23.0 GB
21.3 + 1.7 KV
good
Q5_K_S5.57
25.8 GB
24.2 + 1.7 KV
good
Q5_K_M5.7
26.4 GB
24.7 + 1.7 KV
good
Q6_K6.56
30.1 GB
28.4 + 1.7 KV
excellent
Q8_08.5
38.3 GB
36.6 + 1.7 KV
lossless
FP1616
70.2 GB
68.5 + 1.7 KV
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

Deploying for a team or in production? Size GPUs, cost & scaling in Enterprise →
READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN FALCON-H1 34B NOW

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

Loading ratings...

Benchmarks (9)

Arena Elo1455
IFEval89.4
HumanEval87.2
MBPP83.9
MATH83.8
BBH70.7
MMLU-PRO58.7
GPQA49.7
MUSR5.2

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run falcon:34b-q4_K_M

Tag may need adjustment — check ollama.com/library/falcon for available tags.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

Apple M4 Pro (24GB)
24 GB VRAM • 273 GB/s
APPLE
$1399
NVIDIA L4 24GB
24 GB VRAM • 300 GB/s
NVIDIA
$2500
Apple M2 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M3 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M4 (24GB)
24 GB VRAM • 120 GB/s
APPLE
$699
NVIDIA Tesla M40 24 GB
24 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla P10
24 GB VRAM • 694 GB/s
NVIDIA
NVIDIA Tesla P40
24 GB VRAM • 347 GB/s
NVIDIA
NVIDIA RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA L40 CNX
24 GB VRAM • 864 GB/s
NVIDIA
$5000
NVIDIA L40G
24 GB VRAM • 864 GB/s
NVIDIA
$5000

Find the best GPU for Falcon-H1 34B

Build Hardware for Falcon-H1 34B

Falcon-H1 with hybrid SSM+attention architecture. Strong math and coding.

▸ SPEC SHEET

Falcon-H1 34B34B Dense.

▸ SPECIFICATIONS
PARAMETERS
34B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
32K tokens
CAPABILITIES
chat, coding, reasoning, math
RELEASE DATE
2025-07-30
PROVIDER
TII
FAMILY
falcon
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2514.3 GB82%
IQ3_XS3.515.4 GB84%
Q3_K_S3.6416.0 GB85%
IQ3_M3.7616.5 GB86%
Q3_K_M417.5 GB88%
Q3_K_L4.318.8 GB90%
IQ4_XS4.4619.4 GB92%
Q4_K_S4.6720.3 GB93%
Q4_K_M4.8921.3 GB94%
Q5_K_S5.5724.2 GB96%
Q5_K_M5.724.7 GB96%
Q6_K6.5628.4 GB97%
Q8_08.536.6 GB100%
FP161668.5 GB100%
§ 01BENCHMARK SCORES
HumanEval87.2
MMLU-PRO58.7
MATH83.8
IFEval89.4
BBH70.7
GPQA49.7
MUSR5.2
MBPP83.9
Arena Elo1455.0
§ 02RUN COMMAND

Run Falcon-H1 34B locally with Ollama — needs 21.3 GB VRAM at Q4_K_M:

$ollama run falcon-h1:34b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M