Agnes 3.0 Flash
Agnes 3.0 Flash by Sapiens AI is a high-speed frontier reasoning model with 1.0M context window and 234 tokens/sec throughput.
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Gli assi radar sono approssimati dai punteggi di categoria dove mancano misurazioni dirette — vedi Metodologia.
Punti di forza e compromessi
Dove vince
- 1.0M context — swallows whole repos, codebases or corpora in one pass
- 235 tok/s output — fast enough for real-time agents
- Very low blended price — $0.03/1M mixed tokens
- Cheap prompt-cache reads at $0.01/1M
A cosa fare attenzione
- Architecture and weights undisclosed — API access only
Casi d'uso killer
Quickstart per sviluppatori e API
OPENROUTER_API_KEY — ottieni una chiave APIcurl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "content-type: application/json" \
-d '{
"model": "agnes/agnes-3-0-flash",
"messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key=os.environ["OPENROUTER_API_KEY"],
)
resp = client.chat.completions.create(
model="agnes/agnes-3-0-flash",
messages=[{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}],
)
print(resp.choices[0].message.content)const res = await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.OPENROUTER_API_KEY}`,
"content-type": "application/json",
},
body: JSON.stringify({
model: "agnes/agnes-3-0-flash",
messages: [{ role: "user", content: "Refactor this function for O(n) time and explain the change." }],
}),
});
console.log((await res.json()).choices[0].message.content);OpenRouter-compatible endpoint — one API for 300+ models.
Risorse e link ufficiali
Confronta host e latenza
Throughput, TTFT e prezzi cache su Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock e Azure.
Punteggi per Fonte
Punteggi per Categoria
Risultati dei Benchmark
Specifiche live e architettura
- Switchable reasoning effort — trading latency and tokens for accuracy on hard problems.
- Prompt caching supported — cached input reads at $0.01/1M tokens.
Stima bolletta mensile
Cita e incorpora
Loading badge markdown...@misc{llmpodium2026agnes30flash,
title = {Benchmark Analysis and Intelligence Evaluation of Agnes 3.0 Flash},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/agnes-3-0-flash}
}Incorpora il badge del punteggio
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