Qwen3 30B A3B Thinking 2507 APIOPEN WEIGHTS131K context
Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking.
Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).
What is Qwen3 30B A3B Thinking 2507?
Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. The model is designed specifically for “thinking mode,” where internal reasoning traces are separated...
Qwen3 30B A3B Thinking 2507 on the release timeline
Qwen3 30B A3B Thinking 2507 pricing
Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):
| Model | Input / 1M | Output / 1M | Cache read | Cache write | Context |
|---|---|---|---|---|---|
| Qwen3 30B A3B Thinking 2507 | $0.13 | $1.56 | — | — | 131K |
On output price, Qwen3 30B A3B Thinking 2507 is cheaper than 50% of the 309 models in the catalog.
What Qwen3 30B A3B Thinking 2507 costs per month
| Workload | Tokens in / out (monthly) | Est. cost |
|---|---|---|
| Support chatbot | 40M / 12M | $23.92 |
| RAG / knowledge base | 200M / 20M | $57.20 |
| Coding agent | 80M / 25M | $49.40 |
| Batch extraction | 150M / 8M | $31.98 |
| Content generation | 20M / 40M | $65.00 |
Estimate your own monthly cost
Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.
Qwen3 30B A3B Thinking 2507 vs alternatives
| Model | Input / 1M | Output / 1M | Context | Our test |
|---|---|---|---|---|
| Qwen3 30B A3B Thinking 2507 | $0.13 | $1.56 | 131K | — |
| Qwen3.5-27B | $0.20 | $1.56 | 262K | — |
| Qwen3.5 Plus 2026-02-15 | $0.26 | $1.56 | 1M | — |
| Qwen3 VL 30B A3B Thinking | $0.13 | $1.56 | 131K | — |
| Aion-2.0 | $0.80 | $1.60 | 131K | — |
| Aion-RP 1.0 (8B) | $0.80 | $1.60 | 33K | — |
When not to use Qwen3 30B A3B Thinking 2507
- It is served by a single provider, so there is less failover headroom during an outage.
Specs
| Model ID | qwen/qwen3-30b-a3b-thinking-2507 |
| Modality | text->text (input: text) |
| Context window | 131,072 tokens |
| Max output | 32,768 tokens |
| Tool / function calling | ✅ Yes |
| Structured output (JSON) | ✅ Yes |
| Released | 2025-08-28 |
| Knowledge cutoff | 2025-06-30 |
| Open weights | ✅ Qwen/Qwen3-30B-A3B-Thinking-2507 · 213.1K downloads / 377 likes (30d) |
How to call Qwen3 30B A3B Thinking 2507
from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
model="qwen/qwen3-30b-a3b-thinking-2507",
messages=[{"role": "user", "content": "Hello"}],
# supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)curl https://api.datallmlab.com/v1/chat/completions \
-H "Authorization: Bearer YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"qwen/qwen3-30b-a3b-thinking-2507","messages":[{"role":"user","content":"Hello"}]}'import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
model: "qwen/qwen3-30b-a3b-thinking-2507",
messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);The same key routes Qwen3 30B A3B Thinking 2507 and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.
Prompting tips for Qwen3 30B A3B Thinking 2507
- State the goal, not every step. Qwen3 30B A3B Thinking 2507 reasons internally — give it the objective, constraints and success criteria and let it plan the approach; over-scripting each step tends to lower quality. Turn effort up for hard problems.
- Give it real tools. Pass a
tools=[...]schema instead of asking it to "pretend" — let Qwen3 30B A3B Thinking 2507 emit tool calls, execute them, and feed results back for the next turn. - Constrain JSON with a schema. Use
response_format/ structured outputs rather than "reply in JSON" to get valid, parseable objects every time.
Tips are derived from Qwen3 30B A3B Thinking 2507's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.
Open-source tools for Qwen3 30B A3B Thinking 2507
Popular open-source projects for running and building with Qwen3 30B A3B Thinking 2507 — star counts pulled from GitHub (July 2026).
Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.
Migrating to Qwen3 30B A3B Thinking 2507
Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → qwen/qwen3-30b-a3b-thinking-2507. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.
Self-host or use the API?
Qwen3 30B A3B Thinking 2507 ships open weights (Qwen/Qwen3-30B-A3B-Thinking-2507, ~213.1K downloads and 377 likes in the last 30 days), so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 1 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.
Rate limits & reliability
Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.
Related reading
Call Qwen3 30B A3B Thinking 2507 with one key
300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.
Get an API keyCompare pricingFrequently asked questions
What is Qwen3 30B A3B Thinking 2507?
Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. It accepts text input with a 131K-token context window and was released on 2025-08-28. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.
How much does Qwen3 30B A3B Thinking 2507 cost?
On DataLLM Lab it is $0.13 per 1M input tokens and $1.56 per 1M output tokens — cheaper than about 50% of the 309-model catalog on output price. Pay-as-you-go, no subscription.
What is the context window of Qwen3 30B A3B Thinking 2507?
131K tokens, with up to 33K max output tokens.
Is Qwen3 30B A3B Thinking 2507 open source?
Yes — open weights are published on Hugging Face (Qwen/Qwen3-30B-A3B-Thinking-2507), with about 213.1K downloads and 377 likes in the last 30 days. You can self-host it or call it via DataLLM Lab.
How do I call the Qwen3 30B A3B Thinking 2507 API?
Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "qwen/qwen3-30b-a3b-thinking-2507". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.
What are good alternatives to Qwen3 30B A3B Thinking 2507?
Close options by price and capability include Qwen3.5-27B, Qwen3.5 Plus 2026-02-15, Qwen3 VL 30B A3B Thinking — all callable with the same DataLLM Lab key.