gemma-3-27b-it

multimodal

Gemma 3 27B is the flagship multimodal model in Google DeepMind's Gemma 3 family, designed to tackle the most complex challenges in artificial intelligence. With 27 billion parameters and a context window of up to 128K tokens, the model combines high performance with computational efficiency, delivering state-of-the-art results in both text-based and multimodal tasks.

The model is built upon an architecture inherited from Gemini 2.0 and employs advanced distillation techniques along with an optimized attention structure. This allows it to run even on a single GPU while maintaining performance comparable to models that require up to 32 GPUs. Thanks to its extended context window, SigLIP encoder, and "Pan&Scan" technology, the model can process long documents, scientific papers, and images within a single query without losing coherence or response quality. This makes it particularly valuable for legal and technical analysis, medical diagnostics, and content research involving visual elements. Gemma 3 27B supports more than 140 languages, and an improved tokenizer ensures high-quality translation and cross-lingual analysis.

Gemma 3 27B is not just another language model—it is a next-generation AI assistant that combines the power of large-scale models with accessibility and flexibility. Among its peers, it stands out due to its unique combination of efficiency, multimodality, multilingual support, and high performance on a single graphics card.


Announce Date: 12.03.2025
Parameters: 27B
Context: 132K
Layers: 62, using full attention: 10
Attention Type: Sliding Window Attention
Developer: Google DeepMind
Transformers Version: 4.50.0.dev0
License: gemma

Public endpoint

Use our pre-built public endpoints for free to test inference and explore gemma-3-27b-it capabilities. You can obtain an API access token on the token management page after registration and verification.
Model Name Context Type GPU Status Link

API access to gemma-3-27b-it endpoints

There are no public endpoints for this model yet.

Private endpoint

An endpoint is a server with pre-installed software that automatically downloads neural network weights and launches an OpenAI-compatible API to handle incoming requests.

A private endpoint is created within the user's project, belongs exclusively to the user, and is billed per server configuration in accordance with the infrastructure pricing.

We recommend creating private endpoints when you need to:

  • achieve maximum endpoint performance,
  • access the full context window for processing large requests and conversations,
  • ensure maximum security by processing data in a dedicated, isolated environment.

Recommended server configurations for creating a private inference endpoint gemma-3-27b-it

Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa2-4.32.128.160
131,072.0
tensor
4 $1.26 1.134 Launch
teslaa10-3.16.96.160
131,072.0
pipeline
3 $1.34 1.661 Launch
rtx3090-2.16.64.160
131,072.0
tensor
2 $1.56 38.37 1.292 Launch
rtx3090-2.16.64.160.nvlink
131,072.0
tensor
2 $1.56 1.292 Launch
teslaa10-4.12.48.160
131,072.0
tensor
4 $1.57 3.489 Launch
rtx4090-2.16.64.160
131,072.0
tensor
2 $1.92 82.00 1.081 Launch
teslaa100-1.16.64.160
131,072.0
1 $2.37 51.56 3.879 Launch
rtx5090-2.16.64.160
131,072.0
tensor
2 $2.93 53.10 2.249 Launch
h100-1.16.64.160
131,072.0
1 $3.83 49.87 2.661 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 63.37 3.373 Launch
teslaa100-2.24.96.160.nvlink
131,072.0
tensor
2 $4.61 9.389 Launch
h200-1.16.128.160
131,072.0
1 $4.74 5.765 Launch
h200-2.24.256.160.nvlink
131,072.0
tensor
2 $9.40 12.650 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa2-4.32.128.160
131,072.0
tensor
4 $1.26 1.162 Launch
teslaa10-3.16.96.160
131,072.0
pipeline
3 $1.34 1.429 Launch
teslaa10-4.12.48.160
131,072.0
tensor
4 $1.57 3.517 Launch
rtx3090-3.16.96.160
131,072.0
pipeline
3 $2.29 26.92 1.644 Launch
teslaa100-1.16.64.160
131,072.0
1 $2.37 42.43 2.965 Launch
rtx4090-3.16.96.160
131,072.0
pipeline
3 $2.83 25.75 1.602 Launch
rtx3090-4.16.64.160
131,072.0
tensor
4 $2.89 3.833 Launch
rtx5090-2.16.64.160
131,072.0
tensor
2 $2.93 1.648 Launch
rtx3090-4.16.128.160.nvlink
131,072.0
tensor
4 $3.01 3.833 Launch
rtx4090-4.16.64.160
131,072.0
tensor
4 $3.60 3.822 Launch
h100-1.16.64.160
131,072.0
1 $3.83 50.60 2.288 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 75.60 2.999 Launch
teslaa100-2.24.96.160.nvlink
131,072.0
tensor
2 $4.61 8.789 Launch
h200-1.16.128.160
131,072.0
1 $4.74 5.137 Launch
h200-2.24.256.160.nvlink
131,072.0
tensor
2 $9.40 12.238 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-4.16.128.160
131,072.0
tensor
4 $1.75 27.05 1.358 Launch
teslaa100-1.16.128.160
131,072.0
1 $2.50 27.93 1.594 Launch
rtx3090-4.16.96.320
131,072.0
tensor
4 $2.97 29.89 2.137 Launch
rtx3090-4.16.128.160.nvlink
131,072.0
tensor
4 $3.01 2.137 Launch
rtx4090-4.16.96.240
131,072.0
tensor
4 $3.67 40.92 2.122 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 45.07 1.297 Launch
rtx5090-3.16.96.160
131,072.0
pipeline
3 $4.34 1.689 Launch
teslaa100-2.24.96.160.nvlink
131,072.0
tensor
2 $4.61 7.243 Launch
h200-1.16.128.160
131,072.0
1 $4.74 4.122 Launch
rtx5090-4.16.128.160
131,072.0
tensor
4 $5.74 4.473 Launch
h100-2.24.256.160
131,072.0
tensor
2 $7.84 4.968 Launch
h200-2.24.256.160.nvlink
131,072.0
tensor
2 $9.40 11.176 Launch

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