How much does Ling-3.0-Flash cost?

Ling-3.0-Flash is published as open weights (MIT) — there is no per-token API price. You self-host the model and pay infrastructure cost (GPU rental and operating overhead). Effective cost on commodity 24-48GB GPUs typically lands at $0.10-$0.50 per million output tokens.

What is the context window of Ling-3.0-Flash?

Ling-3.0-Flash supports a context window of 256K tokens (256,000 tokens) and can generate up to 16K output tokens per request.

What is Ling-3.0-Flash best for?

Ling-3.0-Flash is best for: Efficient MoE alternative to trillion-param flagships. It supports chat, function_calling, code capabilities. It is open-source under the MIT license.

Ling-3.0-Flash

Ant Groupopen-source NewOpen Source

First catalog entry for Ant Group's inclusionAI/Bailing team, an actively-shipping open-weight lab (Ling non-thinking, Ring thinking, Ming multimodal families) not previously tracked here despite multiple trillion-parameter MIT-licensed releases through 2026 (Ling-2.5-1T, Ring-2.5-1T, Ling-2.6-1T). Ling-3.0-Flash, announced 27 Jul 2026 with weights open-sourced 5 Aug 2026, is a 124B-total MoE with roughly 5-7B active params per token (sources give both figures; verify against the official Hugging Face card before treating either as final), 256K context, MIT license. Ant claims it matches or beats their own 1T-parameter Ling-2.6-1T flagship on most benchmarks at roughly 1/8th the total parameters — a notable efficiency claim, but independent verification and a standard benchmark table weren't available at the time of writing. Weights ship in BF16 (255GB) and FP8 (128GB) on Hugging Face and ModelScope.

Context Window

256K

tokens

Max Output

16K

tokens

Input Price

Self-host

open weights

Output Price

Self-host

infra cost only

Speed

—

tokens/sec

Released

Aug 2026

2026-08-05

Blended Cost

—

self-host

Value Score

—

n/a self-host

Capabilities

ChatFunction CallingCode Generation

Benchmarks

Quality Index

Price vs Quality

Context Window in Context

Amazon Nova Pro300K
Qwen3.8 27B262K
▸ Ling-3.0-Flash256K
Codestral256K
Nemotron 3 Nano Omni256K
Qwen 3.6 Plus256K
Kimi K2.6256K
Hunyuan Hy3256K

Bar length is logarithmic — each full step is 10× the tokens. Shown against the models with the nearest context windows, not the directory extremes.

Try in Playground Use via Swfte Connect Ant Group Docs

Compare With

Open Source: Licensed under MIT

Пока нет в нашем шлюзе

Ling-3.0-Flash — модель с открытыми весами, её можно запустить самостоятельно. Swfte Connect превращает ваш деплой в управляемый эндпоинт с тем же API, что и у остальных моделей каталога.

Запрос

curl https://api.swfte.com/agents/v2/gateway/chat/completions \
  -H "Authorization: Bearer $SWFTE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "antgroup:ling-3.0-flash",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Разверните эту модель с Swfte Connect

About Ling-3.0-Flash

Ling-3.0-Flash is a open-source AI model by Ant Group, released on August 5, 2026. It supports a context window of 256K tokens and can generate up to 16K output tokens.

Ling-3.0-Flash is published as open weights (MIT) for self-hosting. There is no per-token API price. Cost depends on your inference infrastructure: GPU rental, throughput per GPU, and operating overhead. For commodity 24-48GB GPUs the effective cost typically lands in the $0.10-$0.50 per million output tokens range, well below the cheapest hosted alternatives.

Ling-3.0-Flash is available as an open-source model under the MIT license, meaning you can self-host it for predictable costs or use it through API providers like Swfte Connect.

Using Ling-3.0-Flash with Swfte

Access Ling-3.0-Flash through Swfte Connect, our unified LLM gateway. Connect gives you a single API for 50+ models, with automatic routing, cost optimization, and fallback handling. You can also try Ling-3.0-Flash in our AI Playground before integrating.