Updated minutes ago
NVIDIA

Cosmos 7B

NVIDIA · dense · 7B parameters · 4,096 context

Quality
60.0
Calculate ROI →Compare with othersFine-Tune This Model →

Parameters

7B

Context Window

4K tokens

Architecture

Dense

Best GPU

A10G

Intelligence Brief

Cosmos 7B is a 7B parameter DENSE model from NVIDIA, featuring Grouped Query Attention (GQA) with 28 layers and 3,072 hidden dimensions. With a 4,096 token context window, it supports vision. For self-hosted inference, A10G delivers optimal throughput at $285/month.

Architecture Details

TypeDENSE
Total Parameters7B
Active Parameters7B
Layers28
Hidden Dimension3,072
Attention Heads24
KV Heads8
Head Dimension128
Vocab Size64,000

Memory Requirements

BF16 Weights

14.0 GB

FP8 Weights

7.0 GB

INT4 Weights

3.5 GB

KV-Cache per Token114688 bytes
Activation Estimate0.80 GB

Fits on (single GPU) — most practical first

BEST FITRTX 40608GBINT4RTX 30708GBINT4RTX 308010GBFP8RTX 4070 Ti12GBFP8RTX 4070 Super12GBFP8RTX 306012GBFP8A400016GBFP8RTX 408016GBFP8T416GBFP8V100 16GB16GBFP8RTX 4060 Ti 16GB16GBFP8A216GBFP8

GPU Compatibility Matrix

Cosmos 7B is compatible with 95% of GPU configurations across 41 GPUs at 3 precision levels.

BF16 (Full)
FP8 (Half)
INT4 (Quarter)
Blackwell(7 GPUs)
B200 NVL (pair)360GB
96%
98%
99%
B300288GB
95%
98%
99%
B100 SXM192GB
93%
96%
98%
GB200 NVL72 (per GPU)192GB
93%
96%
98%
Hopper(7 GPUs)
H100 NVL 94GB (per GPU pair)188GB
93%
96%
98%
H200 SXM141GB
90%
95%
98%
H2096GB
85%
93%
96%
GH20096GB
85%
93%
96%
Ada Lovelace(11 GPUs)
L40S48GB
71%
85%
93%
L4048GB
71%
85%
93%
RTX 6000 Ada48GB
71%
85%
93%
L2048GB
71%
85%
93%
Ampere(16 GPUs)
A100 80GB SXM80GB
83%
91%
96%
A100 80GB PCIe80GB
83%
91%
96%
A1664GB
78%
89%
95%
RTX A600048GB
71%
85%
93%
Legend:No fitVery tightTightModerateGoodExcellent

GPU Recommendations

A10Goptimal

BF16 · 1 GPU · vllm

100/100

score

Throughput

231.4 tok/s

Latency (ITL)

4.3ms

Est. TTFT

1ms

Cost/Month

$285

Cost/M Tokens

$0.47

Use this config →
A30optimal

BF16 · 1 GPU · vllm

100/100

score

Throughput

359.9 tok/s

Latency (ITL)

2.8ms

Est. TTFT

0ms

Cost/Month

$332

Cost/M Tokens

$0.35

Use this config →
RTX 4090optimal

BF16 · 1 GPU · vllm

100/100

score

Throughput

388.8 tok/s

Latency (ITL)

2.6ms

Est. TTFT

0ms

Cost/Month

$370

Cost/M Tokens

$0.36

Use this config →

Deployment Options

API

API Deployment

No API pricing available

Self-Hosted

Single GPU

A10G

$285/mo

Min VRAM: 7 GB

Scale

Multi-GPU

RTX 3080 x2

452.6 tok/s

TP· $266/mo

Open Full Calculator →

API Pricing Comparison

No API pricing data available for this model.

Performance Estimates

Throughput by GPU

A10G
231.4 tok/s
A30
359.9 tok/s
RTX 4090
388.8 tok/s

VRAM Breakdown (A10G, BF16)

Weights
Act
Weights 14.0 GBKV-Cache 1.9 GBActivations 6.4 GBOverhead 1.1 GB

Precision Impact

bf16

14.0 GB

weights/GPU

~231.4 tok/s

fp8

7.0 GB

weights/GPU

int4

3.5 GB

weights/GPU

Capabilities

Features

✗ Tool Use✓ Vision✗ Code✗ Math✗ Reasoning✗ Multilingual✗ Structured Output

Supported Frameworks

tensorrt-llm

Supported Precisions

BF16 (default)FP8INT4

Where to Deploy Cosmos 7B

Similar Models

OLMo 2 7B

7B params · dense

Quality: 50

Lower qualityCompare →

Command R 7B

7B params · dense

Quality: 68

from $0.15/M

Larger context, Higher qualityCompare →

Falcon 7B

7B params · dense

Quality: 37

from $0.15/M

Lower qualityCompare →

Zephyr 7B

7B params · dense

Quality: 50

Larger context, Lower qualityCompare →

Vicuna 7B

7B params · dense

Quality: 50

Lower qualityCompare →

Frequently Asked Questions

How much VRAM does Cosmos 7B need for inference?

Cosmos 7B requires approximately 14.0 GB of VRAM at BF16 precision, 7.0 GB at FP8, or 3.5 GB at INT4 quantization. Additional VRAM is needed for KV-cache (114688 bytes per token) and activations (~0.80 GB).

What is the best GPU for Cosmos 7B?

The top recommended GPU for Cosmos 7B is the A10G using BF16 precision. It achieves approximately 231.4 tokens/sec at an estimated cost of $285/month ($0.47/M tokens). Score: 100/100.

How much does Cosmos 7B inference cost?

Cosmos 7B inference costs vary by provider and GPU setup. Use our calculator for detailed cost estimates across all providers.