Ling 3.1 Flash
01.AI’s flash-tier frontier model — high throughput at minimal per-token cost.
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Os eixos do radar são aproximados a partir dos scores de categoria quando faltam medições diretas — veja Metodologia.
Pontos fortes e trade-offs
Onde vence
- 175 tok/s — top-tier flash throughput
- $0.31 blended — among the cheapest frontier-adjacent models
- Strong math/coding for a speed-tier model
Pontos de atenção
- No dedicated reasoning mode
- Text-only — no vision or audio
- Weakest on long agentic traces
Casos de uso matadores
Quickstart do desenvolvedor e API
OPENROUTER_API_KEY — obter uma chave de APIcurl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "content-type: application/json" \
-d '{
"model": "inclusionAI/ling-3-1-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="inclusionAI/ling-3-1-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: "inclusionAI/ling-3-1-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.
Recursos e links oficiais
Comparar hosts e latência
Throughput, TTFT e preços de cache na Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock e Azure.
Pontuações por fonte
Pontuações por categoria
Resultados de benchmarks
Especificações ao vivo e arquitetura
- Sparse MoE tuned for serving density
- 175 tok/s sustained output
- 131K context with cheap cache reads
- Non-reasoning fast path — no thinking tokens burned
Fatura mensal estimada
Citar e incorporar
Loading badge markdown...@misc{llmpodium2026ling31flash,
title = {Benchmark Analysis and Intelligence Evaluation of Ling 3.1 Flash},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/ling-3-1-flash}
}Incorporar selo de pontuação
Adicione um selo de Podium Score ao seu README no GitHub ou Hugging Face — ele aponta para o ranking ao vivo.
Loading badge snippet...Loading badge snippet...Mais de Ling
Modelos alternativos
Principais alternativas para Ling 3.1 Flash com base em recursos, preço e benchmarks.