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Cerebras

BTLM 3B

Cerebras · dense · 3B parameters · 8,192 context

Quality
50.0

Parameters

3B

Context Window

8K tokens

Architecture

Dense

Best GPU

RTX 4070 Ti

Intelligence Brief

BTLM 3B is a 3B parameter DENSE model from Cerebras, featuring Multi-Head Attention (MHA) with 32 layers and 2,560 hidden dimensions. With a 8,192 token context window, it supports code. For self-hosted inference, RTX 4070 Ti delivers optimal throughput at $237/month.

Architecture Details

TypeDENSE
Total Parameters3B
Active Parameters3B
Layers32
Hidden Dimension2,560
Attention Heads32
KV Heads32
Head Dimension80
Vocab Size50,257

Memory Requirements

BF16 Weights

6.0 GB

FP8 Weights

3.0 GB

INT4 Weights

1.5 GB

KV-Cache per Token163840 bytes
Activation Estimate0.30 GB

GPU Compatibility Matrix

BTLM 3B is compatible with 100% of GPU configurations across 41 GPUs at 3 precision levels.

BF16 (Full)
FP8 (Half)
INT4 (Quarter)
Blackwell(7 GPUs)
B200 NVL (pair)360GB
B300288GB
B100 SXM192GB
GB200 NVL72 (per GPU)192GB
Hopper(7 GPUs)
H100 NVL 94GB (per GPU pair)188GB
H200 SXM141GB
H2096GB
GH20096GB
Ada Lovelace(11 GPUs)
L40S48GB
L4048GB
RTX 6000 Ada48GB
L2048GB
Ampere(16 GPUs)
A100 80GB SXM80GB
A100 80GB PCIe80GB
A1664GB
RTX A600048GB
Legend:No fitVery tightTightModerateGoodExcellent

GPU Recommendations

RTX 4070 Tioptimal

BF16 · 1 GPU · vllm

100/100

score

Throughput

408.2 tok/s

Latency (ITL)

2.4ms

Est. TTFT

0ms

Cost/Month

$237

Cost/M Tokens

$0.22

Use this config →
RTX 3080optimal

BF16 · 1 GPU · vllm

100/100

score

Throughput

615.6 tok/s

Latency (ITL)

1.6ms

Est. TTFT

0ms

Cost/Month

$133

Cost/M Tokens

$0.08

Use this config →
RTX 4070 Superoptimal

BF16 · 1 GPU · vllm

100/100

score

Throughput

408.2 tok/s

Latency (ITL)

2.4ms

Est. TTFT

0ms

Cost/Month

$209

Cost/M Tokens

$0.19

Use this config →

Deployment Options

API

API Deployment

No API pricing available

Self-Hosted

Single GPU

RTX 4070 Ti

$237/mo

Min VRAM: 3 GB

Scale

Multi-GPU

RTX 4070 Ti

408.2 tok/s

Best available config

API Pricing Comparison

No API pricing data available for this model.

Performance Estimates

Throughput by GPU

RTX 4070 Ti
408.2 tok/s
RTX 3080
615.6 tok/s
RTX 4070 Super
408.2 tok/s

VRAM Breakdown (RTX 4070 Ti, BF16)

Weights
KV
Act
Weights 6.0 GBKV-Cache 5.4 GBActivations 2.4 GBOverhead 0.5 GB

Precision Impact

bf16

6.0 GB

weights/GPU

~408.2 tok/s

fp8

3.0 GB

weights/GPU

int4

1.5 GB

weights/GPU

Capabilities

Features

Tool Use Vision Code Math Reasoning Multilingual Structured Output

Supported Frameworks

vllmtgi

Supported Precisions

BF16 (default)FP8INT4

Where to Deploy BTLM 3B

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Frequently Asked Questions

How much VRAM does BTLM 3B need for inference?

BTLM 3B requires approximately 6.0 GB of VRAM at BF16 precision, 3.0 GB at FP8, or 1.5 GB at INT4 quantization. Additional VRAM is needed for KV-cache (163840 bytes per token) and activations (~0.30 GB).

What is the best GPU for BTLM 3B?

The top recommended GPU for BTLM 3B is the RTX 4070 Ti using BF16 precision. It achieves approximately 408.2 tokens/sec at an estimated cost of $237/month ($0.22/M tokens). Score: 100/100.

How much does BTLM 3B inference cost?

BTLM 3B inference costs vary by provider and GPU setup. Use our calculator for detailed cost estimates across all providers.