reflection/beam-1.0-501b-a23b
Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active parameters per token, and a...
A dedicated public landing page for this synced catalog row.
Synced from the active catalog
Validated for gateway requests
Charged from your UAI balance
Same API key and billing flow
This page exists for direct linking, onboarding, and SEO. The same model row powers /v1/models, the public catalog, the app pricing screen, and request validation for /v1/chat/completions.
The same model route, but with one account, one balance, and one API shape.
Use Reflection: Beam 1.0 501B A23B for multi-step prompts, planning, and deeper analysis while keeping the same OpenAI-compatible UAI endpoint.
Reflection: Beam 1.0 501B A23B exposes 1.0M tokens, which makes it a good fit for large documents, transcripts, and retrieval-heavy chat flows.
Tool and function-style parameters stay available through the same UAI request surface, so agent stacks do not need a separate provider integration.
Current synced numbers for this exact model row.
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Use this model with your UAI key over the standard OpenAI-compatible route.
Create a key in API Keys, then send requests to https://uai.sh/v1/chat/completions.
curl https://uai.sh/v1/chat/completions \
-H "Authorization: Bearer uai-YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "reflection/beam-1.0-501b-a23b",
"messages": [{"role": "user", "content": "Say hi in one short sentence."}],
"stream": false
}'
from openai import OpenAI
client = OpenAI(base_url="https://uai.sh/v1", api_key="uai-YOUR_API_KEY")
response = client.chat.completions.create(
model="reflection/beam-1.0-501b-a23b",
messages=[{"role": "user", "content": "Say hi in one short sentence."}],
stream=False
)
print(response.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://uai.sh/v1",
apiKey: "uai-YOUR_API_KEY"
});
const response = await client.chat.completions.create({
model: "reflection/beam-1.0-501b-a23b",
messages: [{ role: "user", content: "Say hi in one short sentence." }],
stream: false
});
console.log(response.choices[0].message.content);
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