FitMyLLM
Sarvam AI/Dense

Sarvam AISarvam 30B

Indian multilingual model. Strong Hindi, Tamil, Telugu, Bengali + English. Apache 2.0.

chatmultilingual
32.15B
Parameters
32K
Context length
14
Benchmarks
14
Quantizations
Architecture
Dense
Released
2026-03-06
Layers
19
KV Heads
4
Head Dim
64
Family
other

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
IQ3_XXS3.25
13.8 GB
13.5 + 0.2 KV
low
IQ3_XS3.5
14.8 GB
14.6 + 0.2 KV
low
Q3_K_S3.64
15.3 GB
15.1 + 0.2 KV
low
IQ3_M3.76
15.8 GB
15.6 + 0.2 KV
low
Q3_K_M4
16.8 GB
16.6 + 0.2 KV
low
Q3_K_L4.3
18.0 GB
17.8 + 0.2 KV
moderate
IQ4_XS4.46
18.6 GB
18.4 + 0.2 KV
moderate
Q4_K_S4.67
19.5 GB
19.3 + 0.2 KV
moderate
Q4_K_M4.89
20.4 GB
20.1 + 0.2 KV
good
Q5_K_S5.57
23.1 GB
22.9 + 0.2 KV
good
Q5_K_M5.7
23.6 GB
23.4 + 0.2 KV
good
Q6_K6.56
27.1 GB
26.9 + 0.2 KV
excellent
Q8_08.5
34.9 GB
34.6 + 0.2 KV
lossless
FP1616
65.0 GB
64.8 + 0.2 KV
lossless

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

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Community Ratings

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Benchmarks (14)

MATH97.0
MBPP92.7
HumanEval92.1
MMLU-PRO80.0
AIME80.0
GPQA Diamond66.5
τ²-Bench34.5
SWE-bench34.0
IFBench26.5
SciCode19.2
AA Intelligence12.3
AA Coding7.9
HLE7.0
Terminal-Bench2.3

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run other:32b-q4_K_M

Tag may need adjustment — check ollama.com/library/other 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 Sarvam 30B

Build Hardware for Sarvam 30B
▸ SPEC SHEET

Sarvam 30B32.15B Dense.

▸ SPECIFICATIONS
PARAMETERS
32.15B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
32K tokens
CAPABILITIES
chat, multilingual
RELEASE DATE
2026-03-06
PROVIDER
Sarvam AI
FAMILY
other
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2513.5 GB82%
IQ3_XS3.514.6 GB84%
Q3_K_S3.6415.1 GB85%
IQ3_M3.7615.6 GB86%
Q3_K_M416.6 GB88%
Q3_K_L4.317.8 GB90%
IQ4_XS4.4618.4 GB92%
Q4_K_S4.6719.3 GB93%
Q4_K_M4.8920.1 GB94%
Q5_K_S5.5722.9 GB96%
Q5_K_M5.723.4 GB96%
Q6_K6.5626.9 GB97%
Q8_08.534.6 GB100%
FP161664.8 GB100%
§ 01BENCHMARK SCORES
HumanEval92.1
MMLU-PRO80.0
MATH97.0
MBPP92.7
SWE-bench34.0
AIME80.0
GPQA Diamond66.5
HLE7.0
AA Intelligence12.3
AA Coding7.9
aa_ifbench26.5
aa_terminal_bench2.3
aa_tau234.5
aa_scicode19.2
§ 03COMPATIBLE GPUs
30 @ Q4_K_M