Gemma-3-27B

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: 131K
Attention Type: Sliding Window Attention
VRAM requirements: 26.2 GB using 4 bits quantization
Developer: Google DeepMind
Transformers Version: 4.50.0.dev0
Ollama Version: 0.6
License: gemma

Public endpoint

Use our pre-built public endpoints to test inference and explore Gemma-3-27B capabilities.
Model Name Context Type GPU TPS Status Link
google/gemma-3-27b-it 128,000.0 Public 2×RTX4090 48.60 AVAILABLE try

API access to Gemma-3-27B endpoints

curl https://chat.immers.cloud/v1/endpoints/Gemma-3-27b-it/generate/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer USER_API_KEY" \
-d '{"model": "Gemma-3-27b-it", "messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Say this is a test"}
], "temperature": 0, "max_tokens": 150}'
$response = Invoke-WebRequest https://chat.immers.cloud/v1/endpoints/Gemma-3-27b-it/generate/chat/completions `
-Method POST `
-Headers @{
"Authorization" = "Bearer USER_API_KEY"
"Content-Type" = "application/json"
} `
-Body (@{
model = "Gemma-3-27b-it"
messages = @(
@{ role = "system"; content = "You are a helpful assistant." },
@{ role = "user"; content = "Say this is a test" }
)
} | ConvertTo-Json)
($response.Content | ConvertFrom-Json).choices[0].message.content
#!pip install OpenAI --upgrade

from openai import OpenAI

client = OpenAI(
api_key="USER_API_KEY",
base_url="https://chat.immers.cloud/v1/endpoints/Gemma-3-27b-it/generate/",
)

chat_response = client.chat.completions.create(
model="Gemma-3-27b-it",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Say this is a test"},
]
)
print(chat_response.choices[0].message.content)

Private server

Rent your own physically dedicated instance with hourly or long-term monthly billing.

We recommend deploying private instances in the following scenarios:

  • maximize endpoint performance,
  • enable full context for long sequences,
  • ensure top-tier security for data processing in an isolated, dedicated environment,
  • use custom weights, such as fine-tuned models or LoRA adapters.

Recommended configurations for hosting Gemma-3-27B

Prices:
Name vCPU RAM, MB Disk, GB GPU Price, hour
teslaa2-2.16.32.160 16 32768 160 2 $0.57 Launch
teslat4-2.16.32.160 16 32768 160 2 $0.80 Launch
teslaa10-2.16.64.160 16 65536 160 2 $0.93 Launch
rtx2080ti-3.16.64.160 16 65536 160 3 $0.95 Launch
teslav100-1.12.64.160 12 65536 160 1 $1.20 Launch
rtx3080-3.16.64.160 16 65536 160 3 $1.43 Launch
rtx5090-1.16.64.160 16 65536 160 1 $1.59 Launch
rtx3090-2.16.64.160 16 65536 160 2 $1.67 Launch
rtx4090-2.16.64.160 16 65536 160 2 $2.19 Launch
teslaa100-1.16.64.160 16 65536 160 1 $2.58 Launch
teslah100-1.16.64.160 16 65536 160 1 $5.11 Launch
Prices:
Name vCPU RAM, MB Disk, GB GPU Price, hour
teslaa10-2.16.64.160 16 65536 160 2 $0.93 Launch
rtx2080ti-4.16.64.160 16 65536 160 4 $1.18 Launch
teslat4-4.16.64.160 16 65536 160 4 $1.48 Launch
rtx3090-2.16.64.160 16 65536 160 2 $1.67 Launch
rtx4090-2.16.64.160 16 65536 160 2 $2.19 Launch
teslav100-2.16.64.240 16 65535 240 2 $2.22 Launch
teslaa100-1.16.64.160 16 65536 160 1 $2.58 Launch
rtx5090-2.16.64.160 16 65536 160 2 $2.93 Launch
teslah100-1.16.64.160 16 65536 160 1 $5.11 Launch
Prices:
Name vCPU RAM, MB Disk, GB GPU Price, hour
teslaa10-3.16.96.160 16 98304 160 3 $1.34 Launch
rtx3090-3.16.96.160 16 98304 160 3 $2.45 Launch
teslaa100-1.16.128.160 16 131072 160 1 $2.71 Launch
rtx4090-3.16.96.160 16 98304 160 3 $3.23 Launch
rtx5090-3.16.96.160 16 98304 160 3 $4.34 Launch
teslah100-1.16.128.160 16 131072 160 1 $5.23 Launch

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