Japanese StableLM 70B
Stability AI · dense · 70B parameters · 8,192 context
Parameters
70B
Context Window
8K tokens
Architecture
Dense
Best GPU
H200 SXM
Intelligence Brief
Japanese StableLM 70B is a 70B parameter DENSE model from Stability AI, featuring Grouped Query Attention (GQA) with 80 layers and 8,192 hidden dimensions. With a 8,192 token context window, it supports multilingual. For self-hosted inference, H200 SXM delivers optimal throughput at $2553/month.
Architecture Details
Memory Requirements
BF16 Weights
140.0 GB
FP8 Weights
70.0 GB
INT4 Weights
35.0 GB
GPU Compatibility Matrix
Japanese StableLM 70B is compatible with 38% of GPU configurations across 41 GPUs at 3 precision levels.
GPU Recommendations
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
560.0 tok/s
Latency (ITL)
1.8ms
Est. TTFT
0ms
Cost/Month
$2553
Cost/M Tokens
$1.73
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
478.0 tok/s
Latency (ITL)
2.1ms
Est. TTFT
0ms
Cost/Month
$940
Cost/M Tokens
$0.75
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
478.0 tok/s
Latency (ITL)
2.1ms
Est. TTFT
0ms
Cost/Month
$2838
Cost/M Tokens
$2.26
Deployment Options
API Deployment
No API pricing available
Single GPU
H200 SXM
$2553/mo
Min VRAM: 70 GB
Multi-GPU
H100 SXM x2
560.0 tok/s
TP· $3587/mo
API Pricing Comparison
No API pricing data available for this model.
Performance Estimates
Throughput by GPU
VRAM Breakdown (H200 SXM, FP8)
Precision Impact
bf16
140.0 GB
weights/GPU
fp8
70.0 GB
weights/GPU
~560.0 tok/s
int4
35.0 GB
weights/GPU
Capabilities
Features
Supported Frameworks
Supported Precisions
Where to Deploy Japanese StableLM 70B
Self-Hosted Infrastructure
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Frequently Asked Questions
How much VRAM does Japanese StableLM 70B need for inference?
Japanese StableLM 70B requires approximately 140.0 GB of VRAM at BF16 precision, 70.0 GB at FP8, or 35.0 GB at INT4 quantization. Additional VRAM is needed for KV-cache (655360 bytes per token) and activations (~3.00 GB).
What is the best GPU for Japanese StableLM 70B?
The top recommended GPU for Japanese StableLM 70B is the H200 SXM using FP8 precision. It achieves approximately 560.0 tokens/sec at an estimated cost of $2553/month ($1.73/M tokens). Score: 100/100.
How much does Japanese StableLM 70B inference cost?
Japanese StableLM 70B inference costs vary by provider and GPU setup. Use our calculator for detailed cost estimates across all providers.