Skip to content

DeepSeek Coder V2 236B vs Code Llama 34B

DeepSeek
DeepSeek Coder V2 236B

DeepSeek · 236B params · Quality: 50

Meta
Code Llama 34B

Meta · 34B params · Quality: 55

Architecture Comparison

SpecDeepSeek Coder V2 236BCode Llama 34B
TypeMOEDENSE
Total Parameters236B34B
Active Parameters21B34B
Layers6048
Hidden Dimension5,1208,192
Attention Heads12864
KV Heads18
Context Length131,072100,000
Precision (default)BF16BF16
Total Experts128N/A
Active Experts6N/A

Memory Requirements

PrecisionDeepSeek Coder V2 236BCode Llama 34B
BF16 Weights472.0 GB68.0 GB
FP8 Weights236.0 GB34.0 GB
INT4 Weights118.0 GB17.0 GB
KV-Cache / Token30720 B196608 B
Activation Estimate3.00 GB2.00 GB

Minimum GPUs Needed (BF16)

H100 SXM7 GPUs1 GPU
L40SN/A2 GPUs

Quality Benchmarks

BenchmarkDeepSeek Coder V2 236BCode Llama 34B
Overall5055
MMLUN/A56.0
HumanEvalN/A48.8
GSM8KN/A45.0
MT-BenchN/A68.0

DeepSeek Coder V2 236B

Code Llama 34B

MMLU
56.0
HumanEval
48.8
GSM8K
45.0
MT-Bench
68.0

Capabilities

FeatureDeepSeek Coder V2 236BCode Llama 34B
Tool Use✓ Yes✗ No
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✗ No✗ No
Multilingual✓ Yes✗ No
Structured Output✓ Yes✗ No

API Pricing Comparison

Cheapest Output (DeepSeek Coder V2 236B)

$0.28/M

Input: $0.14/M

Cheapest Output (Code Llama 34B)

$0.78/M

Input: $0.78/M

ProviderDeepSeek Coder V2 236B In $/MOut $/MCode Llama 34B In $/MOut $/M
deepseek$0.14$0.28
together$0.90$0.90$0.78$0.78

Recommendation Summary

  • Code Llama 34B scores higher on overall quality (55 vs 50).
  • DeepSeek Coder V2 236B is cheaper per output token ($0.28/M vs $0.78/M).
  • Code Llama 34B has a smaller memory footprint (68.0 GB vs 472.0 GB BF16), making it easier to deploy on fewer GPUs.
  • DeepSeek Coder V2 236B supports a longer context window (131,072 vs 100,000 tokens).
  • DeepSeek Coder V2 236B uses MOE architecture while Code Llama 34B uses DENSE. MoE models activate fewer parameters per token, improving inference efficiency.

Compare Other Models