Core Concepts
A context window defines the maximum amount of text (in tokens) that a model can process in a single inference session. This includes both the input prompt history and the model's output tokens.
Cortiqa's active flagship model, GPT-OSS 120B (openai/gpt-oss-120b), features an expansive 131,072 token (131K) context window running with KV-cache optimization on Cortiqa LPU hardware. This allows you to ingest entire code repositories, research papers, or dozens of chat turns in a single prompt.
| Model | Context Window | Max Output | Status |
|---|---|---|---|
GPT-OSS 120B (openai/gpt-oss-120b) | 131,072 tokens (131K) | 4,096 tokens | Active / Production |
Falin 01 (falin-01) | 128,000 tokens (128K) | 4,096 tokens | Coming Soon |
Falin Pro (falin-pro) | 200,000 tokens (200K) | 8,192 tokens | Coming Soon |
Falin Vision (falin-vision) | 128,000 tokens (128K) | 4,096 tokens | Coming Soon |
Falin Ultra (falin-ultra) | 256,000 tokens (256K) | 8,192 tokens | Coming Soon |
Every response returns precise token consumption metrics in the usage payload:
from cortiqa import Cortiqa
client = Cortiqa()
response = client.chat.completions.create(
model="openai/gpt-oss-120b",
messages=[{"role": "user", "content": "Analyze this query."}]
)
print(f"Prompt tokens: {response.usage.prompt_tokens}")
print(f"Completion tokens: {response.usage.completion_tokens}")
print(f"Total tokens: {response.usage.total_tokens}")