CodeGemma 7B
Google · dense · 8.5B parameters · 8,192 context
Parameters
8.5B
Context Window
8K tokens
Architecture
Dense
Best GPU
A30
Quality Score
52/100
Intelligence Brief
CodeGemma 7B is a 8.5B parameter DENSE model from Google, featuring Multi-Head Attention (MHA) with 28 layers and 3,072 hidden dimensions. With a 8,192 token context window, it supports code, math. On standardized benchmarks, it achieves MMLU 56, HumanEval 44, GSM8K 50. For self-hosted inference, A30 delivers optimal throughput at $332/month.
Architecture Details
Memory Requirements
BF16 Weights
17.0 GB
FP8 Weights
8.5 GB
INT4 Weights
4.3 GB
GPU Compatibility Matrix
CodeGemma 7B is compatible with 90% of GPU configurations across 41 GPUs at 3 precision levels.
GPU Recommendations
BF16 · 1 GPU · vllm
100/100
score
Throughput
266.7 tok/s
Latency (ITL)
3.7ms
Est. TTFT
1ms
Cost/Month
$332
Cost/M Tokens
$0.47
BF16 · 1 GPU · vllm
100/100
score
Throughput
288.2 tok/s
Latency (ITL)
3.5ms
Est. TTFT
1ms
Cost/Month
$370
Cost/M Tokens
$0.49
BF16 · 1 GPU · vllm
100/100
score
Throughput
267.6 tok/s
Latency (ITL)
3.7ms
Est. TTFT
1ms
Cost/Month
$180
Cost/M Tokens
$0.26
Deployment Options
API Deployment
No API pricing available
Single GPU
A30
$332/mo
Min VRAM: 9 GB
Multi-GPU
RTX 3060 x2
162.3 tok/s
TP· $114/mo
API Pricing Comparison
No API pricing data available for this model.
Performance Estimates
Throughput by GPU
VRAM Breakdown (A30, BF16)
Precision Impact
bf16
17.0 GB
weights/GPU
~266.7 tok/s
fp8
8.5 GB
weights/GPU
int4
4.3 GB
weights/GPU
Quality Benchmarks
Capabilities
Features
Supported Frameworks
Supported Precisions
Where to Deploy CodeGemma 7B
Self-Hosted Infrastructure
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Frequently Asked Questions
How much VRAM does CodeGemma 7B need for inference?
CodeGemma 7B requires approximately 17.0 GB of VRAM at BF16 precision, 8.5 GB at FP8, or 4.3 GB at INT4 quantization. Additional VRAM is needed for KV-cache (229376 bytes per token) and activations (~0.80 GB).
What is the best GPU for CodeGemma 7B?
The top recommended GPU for CodeGemma 7B is the A30 using BF16 precision. It achieves approximately 266.7 tokens/sec at an estimated cost of $332/month ($0.47/M tokens). Score: 100/100.
How much does CodeGemma 7B inference cost?
CodeGemma 7B inference costs vary by provider and GPU setup. Use our calculator for detailed cost estimates across all providers.