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qwen3-30b-a3b-instruct-2507

Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and agentic tool use. Post-trained on instruction data, it demonstrates competitive performance across reasoning (AIME, ZebraLogic), coding (MultiPL-E, LiveCodeBench), and alignment (IFEval, WritingBench) benchmarks. It outperforms its non-instruct variant on subjective and open-ended tasks while retaining strong factual and coding performance.

VisionTool callingCachingJSON schema
Try qwen3-30b-a3b-instruct-2507CompareDocs

Specifications

Context window131K tokens
Max output66K tokens
API typechat
AddedJul 31, 2025
Model IDalibaba/qwen3-30b-a3b-instruct-2507
Data retentionNo
Used for trainingNo
Provider location🇸🇬 Singapore
Privacy policyAlibaba Cloud Privacy Policy→

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model. Check the base model page or the Alibaba Cloud models overview.

Pricing

Input / 1M
$0.20
Output / 1M
$0.80
Cache write / 1M
$0.80
Cache read / 1M
$0.20
Estimated cost
100K input + 10K output$0.0280
1M input + 100K output$0.28
10M input + 1M output$2.80

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to alibaba/qwen3-30b-a3b-instruct-2507.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="alibaba/qwen3-30b-a3b-instruct-2507",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

Other Alibaba Cloud models

qwen3.7-plus
1.0M ctx$0.32/1M
Coding 47
qwen3.6-plus
1M ctx$0.50/1M
Coding 43
qwen3.7-max
1.0M ctx$2.50/1M
Coding 50
qwen3-max
262K ctx$0.86/1M
Coding 31
qwen3-coder-plus
1.0M ctx$1.00/1M
qwen3-coder-flash
1.0M ctx$0.30/1M

Frequently asked questions

How much does qwen3-30b-a3b-instruct-2507 cost?
qwen3-30b-a3b-instruct-2507 is priced at $0.20 per million input tokens and $0.80 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of qwen3-30b-a3b-instruct-2507?
qwen3-30b-a3b-instruct-2507 has a context window of 131K tokens, with a maximum output of 66K tokens per response. That's roughly 175 words of input you can fit in a single prompt.
What can qwen3-30b-a3b-instruct-2507 do?
qwen3-30b-a3b-instruct-2507 supports vision input, tool calling, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use qwen3-30b-a3b-instruct-2507 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "alibaba/qwen3-30b-a3b-instruct-2507". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run qwen3-30b-a3b-instruct-2507 through Requesty?
Yes. qwen3-30b-a3b-instruct-2507 runs through Requesty's OpenAI-compatible API, served from Alibaba Cloud. You do not host the model yourself: point base_url at Requesty, set the model to "alibaba/qwen3-30b-a3b-instruct-2507", and requests are routed to the upstream provider with automatic failover. The same key gives you 400+ other models too.

Access qwen3-30b-a3b-instruct-2507 through Requesty

One API key, 400+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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