AI 模型情报

Qwen3 30B A3B

alibaba/qwen3-30b-a3b

出品方: Alibaba (Qwen) · 系列: qwen · 发布 2025-04-29 · 知识截止: 2025-04

$0.080
输入 / 1M token
$0.280
输出 / 1M token
41K
上下文长度
16K
最大输出

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

能力清单

工具调用推理结构化输出附件开放权重温度可调
支持模态: 输入 text · 输出 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.

Coding80
  • Tool calling40/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)0/20
  • Provider availability10/10
Agents95
  • Tool calling35/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit10/15
  • Provider availability10/10
JSON / structured output99
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume19/20
Cost efficiency78
  • Headline price (log-scaled)73/95
  • Has prompt-cache pricing5/5
Long context0
  • Context ≥ 100K0/100
Production-readiness94
  • Number of independent providers40/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers4/10
  • 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
$0.54
< $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
$1.08
< $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
$0.30
< $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
$0.92
< $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
$1.13
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定价详情

推荐定价来自 kilo · qwen/qwen3-30b-a3b

$0.080
输入
$0.280
输出
$0.030
缓存读

在 10 家渠道可用

服务商服务商模型 ID输入 / 1M输出 / 1M上下文发布日期
OpenRouter
openrouter
qwen/qwen3-30b-a3b$0.120$0.50041K2025-04-28
Qiniu
qiniu-ai
qwen3-30b-a3bUnknownUnknown40K2025-08-05
NovitaAI
novita-ai
qwen/qwen3-30b-a3b-fp8$0.090$0.45041K2025-04-29
302.AI
302ai
qwen3-30b-a3b$0.110$1.08128K2025-04-29
Cloudflare Workers AI
cloudflare-workers-ai
@cf/qwen/qwen3-30b-a3b-fp8$0.051$0.33533K2025-04-30
Helicone
helicone
qwen3-30b-a3b$0.080$0.29041K2025-06-01
Cloudflare AI Gateway
cloudflare-ai-gateway
workers-ai/@cf/qwen/qwen3-30b-a3b-fp8$0.051$0.340128K2025-11-14
Kilo Gateway
kilo
qwen/qwen3-30b-a3b$0.080$0.28041K2025-04
Jiekou.AI
jiekou
qwen/qwen3-30b-a3b-fp8$0.090$0.45041K2026-01
NanoGPT
nano-gpt
qwen/qwen3-30b-a3b$0.100$0.30041K2025-02-27

各渠道数据存在不一致

  • context_window varies: 128000, 32768, 40000, 40960, 41000
  • release_date varies (span 308d): 2025-02-27, 2025-04, 2025-04-28, 2025-04-29, 2025-04-30, 2025-06-01, 2025-08-05, 2025-11-14, 2026-01
  • modalities varies across offerings

各服务商对此模型的报告值存在差异。上方「核心数据」使用代表性服务商的值;逐项请以下表为准。

Frequently asked questions

How much does Qwen3 30B A3B cost?

Qwen3 30B A3B costs $0.080 per 1M input tokens and $0.280 per 1M output tokens, sourced from kilo. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Qwen3 30B A3B?

Qwen3 30B A3B has a context window of 41K tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.

Does Qwen3 30B A3B support tool calling?

Yes. Qwen3 30B A3B 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 Qwen3 30B A3B support structured output / JSON mode?

Yes. Qwen3 30B A3B 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 Qwen3 30B A3B accept image input?

No. Qwen3 30B A3B only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Qwen3 30B A3B open-weight?

Yes. Qwen3 30B A3B'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 Qwen3 30B A3B?

If Qwen3 30B A3B doesn't fit, consider Qwen3.5 397B-A17B, Qwen3 32B, Qwen3.7 Max. 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.

More Alibaba (Qwen) models

最近更新:

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