Ministral 8B
Mistral AI · dense · 8B parameters · 131,072 context
Parameters
8B
Context Window
128K tokens
Architecture
Dense
Best GPU
A30
Cheapest API
$0.10/M
Intelligence Brief
Ministral 8B is a 8B parameter DENSE model from Mistral AI, featuring Grouped Query Attention (GQA) with 36 layers and 4,096 hidden dimensions. With a 131,072 token context window, it supports tools, structured output, code, math, multilingual. The most cost-effective API deployment is via mistral at $0.10/M output tokens. For self-hosted inference, A30 delivers optimal throughput at $332/month.
Architecture Details
Memory Requirements
BF16 Weights
16.0 GB
FP8 Weights
8.0 GB
INT4 Weights
4.0 GB
GPU Compatibility Matrix
Ministral 8B is compatible with 90% of GPU configurations across 41 GPUs at 3 precision levels.
GPU Recommendations
BF16 · 1 GPU · vllm
100/100
score
Throughput
314.9 tok/s
Latency (ITL)
3.2ms
Est. TTFT
1ms
Cost/Month
$332
Cost/M Tokens
$0.40
BF16 · 1 GPU · vllm
100/100
score
Throughput
340.2 tok/s
Latency (ITL)
2.9ms
Est. TTFT
1ms
Cost/Month
$370
Cost/M Tokens
$0.41
BF16 · 1 GPU · vllm
100/100
score
Throughput
315.9 tok/s
Latency (ITL)
3.2ms
Est. TTFT
1ms
Cost/Month
$180
Cost/M Tokens
$0.22
Deployment Options
API Deployment
mistral
$0.10/M
output tokens
Single GPU
A30
$332/mo
Min VRAM: 8 GB
Multi-GPU
RTX 3060 x2
190.4 tok/s
TP· $114/mo
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| mistral | $0.10 | $0.10 | Cheapest |
Cost Analysis
| Provider | Input $/M | Output $/M | ~Monthly Cost |
|---|---|---|---|
| mistralBest Value | $0.10 | $0.10 | $1 |
Cost per 1,000 Requests
Short (500 tok)
$0.07
via mistral
Medium (2K tok)
$0.28
via mistral
Long (8K tok)
$1.00
via mistral
Performance Estimates
Throughput by GPU
VRAM Breakdown (A30, BF16)
Precision Impact
bf16
16.0 GB
weights/GPU
~314.9 tok/s
fp8
8.0 GB
weights/GPU
int4
4.0 GB
weights/GPU
Capabilities
Features
Supported Frameworks
Supported Precisions
Where to Deploy Ministral 8B
Self-Hosted Infrastructure
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Frequently Asked Questions
How much VRAM does Ministral 8B need for inference?
Ministral 8B requires approximately 16.0 GB of VRAM at BF16 precision, 8.0 GB at FP8, or 4.0 GB at INT4 quantization. Additional VRAM is needed for KV-cache (147456 bytes per token) and activations (~1.00 GB).
What is the best GPU for Ministral 8B?
The top recommended GPU for Ministral 8B is the A30 using BF16 precision. It achieves approximately 314.9 tokens/sec at an estimated cost of $332/month ($0.40/M tokens). Score: 100/100.
How much does Ministral 8B inference cost?
Ministral 8B API inference starts from $0.10/M input tokens and $0.10/M output tokens. Self-hosted inference costs depend on your GPU configuration — use our ROI calculator for a detailed breakdown.