AIモデルインテリジェンス

Ling 3.0 Tiny

openrouter/ling-3-0-tiny

提供： openrouter · ファミリー: ling · リリース 2026-08-06

$0.015
入力 / 100万トークン
$0.045
出力 / 100万トークン
262K
コンテキスト長
250K
最大出力

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

機能一覧

✓ ツール呼び出し✓ 推論✓ 構造化出力✗ 添付✓ オープンウェイト✓ 温度制御
モダリティ: 入力 text · 出力 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding79
  • Tool calling40/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)8/20
  • Provider availability1/10
Agents91
  • Tool calling35/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output100
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume20/20
Cost efficiency96
  • Headline price (log-scaled)91/95
  • Has prompt-cache pricing5/5
Long context61
  • Context window (100K → 2M)51/90
  • Has published price for full window10/10
Production-readiness65
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$0.10
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$0.20
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$0.05
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$0.17
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$0.21
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

料金詳細

推奨料金 (提供元): openrouter · inclusionai/ling-3.0-tiny

$0.015
入力
$0.045
出力
$0.003
キャッシュ読み取り

1 か所で利用可能

プロバイダープロバイダーモデルID入力 / 1M出力 / 1Mコンテキストリリース日
OpenRouter
openrouter
inclusionai/ling-3.0-tiny$0.015$0.045262K2026-08-06

Frequently asked questions

How much does Ling 3.0 Tiny cost?

Ling 3.0 Tiny costs $0.015 per 1M input tokens and $0.045 per 1M output tokens, sourced from openrouter. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Ling 3.0 Tiny?

Ling 3.0 Tiny has a context window of 262K tokens, with a max output of 250K tokens per reply. This is the total combined size of prompt + completion.

Does Ling 3.0 Tiny support tool calling?

Yes. Ling 3.0 Tiny supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Ling 3.0 Tiny support structured output / JSON mode?

Yes. Ling 3.0 Tiny supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Can Ling 3.0 Tiny accept image input?

No. Ling 3.0 Tiny only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Ling 3.0 Tiny open-weight?

Yes. Ling 3.0 Tiny's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to Ling 3.0 Tiny?

If Ling 3.0 Tiny doesn't fit, consider ricursiveAI/Ripple-65B-Preview, Free Models Router, Body Builder (beta). Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Explore more

More openrouter models

Capability lists this model is in

See also

最終更新：

Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.