FitMyLLM
DeepSeek/Dense

DeepSeekDeepSeek Coder 33B

DeepSeek Coder 33B — professional-grade code generation and completion.

coding
33B
Parameters
16K
Context length
7
Benchmarks
14
Quantizations
0
Architecture
Dense
Released
2023-11-02
Layers
62
KV Heads
8
Head Dim
128
Family
deepseek

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
IQ3_XXS3.25
16.8 GB
13.9 + 2.9 KV
low
IQ3_XS3.5
17.8 GB
14.9 + 2.9 KV
low
Q3_K_S3.64
18.4 GB
15.5 + 2.9 KV
low
IQ3_M3.76
18.9 GB
16.0 + 2.9 KV
low
Q3_K_M4
19.9 GB
17.0 + 2.9 KV
low
Q3_K_L4.3
21.1 GB
18.2 + 2.9 KV
moderate
IQ4_XS4.46
21.8 GB
18.9 + 2.9 KV
moderate
Q4_K_S4.67
22.7 GB
19.8 + 2.9 KV
moderate
Q4_K_M4.89
23.6 GB
20.7 + 2.9 KV
good
Q5_K_S5.57
26.4 GB
23.5 + 2.9 KV
good
Q5_K_M5.7
26.9 GB
24.0 + 2.9 KV
good
Q6_K6.56
30.5 GB
27.5 + 2.9 KV
excellent
Q8_08.5
38.5 GB
35.6 + 2.9 KV
lossless
FP1616
69.4 GB
66.5 + 2.9 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 (7)

HumanEval44.5
IFEval41.9
MMLU-PRO41.0
MATH17.1
BBH17.1
MUSR16.1
GPQA4.6

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run deepseek-coder:33b-base-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ 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 DeepSeek Coder 33B

Build Hardware for DeepSeek Coder 33B

DeepSeek Coder 33B — professional-grade code generation and completion.

▸ SPEC SHEET

DeepSeek Coder 33B33B Dense.

▸ SPECIFICATIONS
PARAMETERS
33B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
16K tokens
CAPABILITIES
coding
RELEASE DATE
2023-11-02
PROVIDER
DeepSeek
FAMILY
deepseek
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2513.9 GB82%
IQ3_XS3.514.9 GB84%
Q3_K_S3.6415.5 GB85%
IQ3_M3.7616.0 GB86%
Q3_K_M417.0 GB88%
Q3_K_L4.318.2 GB90%
IQ4_XS4.4618.9 GB92%
Q4_K_S4.6719.8 GB93%
Q4_K_M4.8920.7 GB94%
Q5_K_S5.5723.5 GB96%
Q5_K_M5.724.0 GB96%
Q6_K6.5627.5 GB97%
Q8_08.535.6 GB100%
FP161666.5 GB100%
§ 01BENCHMARK SCORES
HumanEval44.5
MMLU-PRO41.0
MATH17.1
IFEval41.9
BBH17.1
GPQA4.6
MUSR16.1
§ 02RUN COMMAND

Run DeepSeek Coder 33B locally with Ollama — needs 20.7 GB VRAM at Q4_K_M:

$ollama run deepseek-coder:33b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M