Last refreshed 2026-09-24. Next refresh: weekly.
Why use Gemma 2 27B Instruct on Featherless?
Featherless offers Gemma 2 27B Instruct with pay-as-you-go pricing at $0.65/1M input tokens. Featherless is a serverless inference provider for a large catalog of third-party open text-generation models (40,000+).
Compare Gemma 2 27B Instruct across 7 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport FEATHERLESS_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.featherless.ai/v1",google/gemma-2-27b-itRequest example
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.featherless.ai/v1",
api_key=os.environ["FEATHERLESS_API_KEY"],
)
response = client.chat.completions.create(
model="google/gemma-2-27b-it",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "google/gemma-2-27b-it", not the LLMReference slug "gemma-2-27b-it".
- Use exact Featherless catalog id in modelProvider.providerModelId (HF-style org/name). Not interchangeable with LLM Reference slugs.
- The examples expect FEATHERLESS_API_KEY; rename it only if your application config maps the new variable.
Compare Gemma 2 27B Instruct Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| NVIDIA NIM | — | — |
| OpenRouter | $0.65 | $0.65 |
| Fireworks AI | $0.90 | $0.90 |
| Arcee AI | $0.25 | $0.75 |
| Replicate API | $0.40 | $0.40 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.65 |
| Output tokens | $0.65 |
Capabilities
About Gemma 2 27B Instruct
Gemma 2 27B Instruct is a cutting-edge large language model from Google, excelling in text generation, question answering, summarization, and reasoning tasks. It features a decoder-only transformer architecture, utilizing 27 billion parameters, and supports context length processing of up to 8,192 tokens. The model incorporates innovative mechanisms like Grouped Query Attention and Sliding Window Attention to enhance efficiency and effectiveness in handling long texts. Its instruction-tuned variants are designed for improved interaction in conversational tasks, and it benefits from knowledge distillation techniques for enhanced performance. Additionally, Gemma 2 27B Instruct is openly accessible, promoting wider innovation in AI applications.