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Qwen3 235B A22B Instruct 2507

openrouter/qwen3-235b-a22b-07-25

من openrouter · العائلة: qwen · أُصدِر 2025-04-28 · تاريخ المعرفة: 2025-04

⚠ هذا نموذج مُحسَّن من المجتمع أو مشتق — وليس إصدارًا رسميًا من المزود.

$0.150
الإدخال / 1M رمز
$0.850
الإخراج / 1M رمز
262K
نافذة السياق
131K
أقصى إخراج

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

القدرات

✓ استدعاء الأدوات✗ تفكير✓ إخراج منظم✗ المرفقات✓ أوزان مفتوحة✓ التحكم بالحرارة
الوسائط المدعومة: إدخال text · إخراج 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.

Coding69
  • Tool calling40/40
  • Structured output20/20
  • Reasoning0/10
  • Context window (100K → 1M)8/20
  • Provider availability1/10
Agents76
  • Tool calling35/35
  • Structured output25/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output98
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume18/20
Cost efficiency62
  • Headline price (log-scaled)62/95
  • Has prompt-cache pricing0/5
Long context61
  • Context window (100K → 2M)51/90
  • Has published price for full window10/10
Production-readiness50
  • 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)0/15

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
$1.18
< $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
$2.35
< $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
$0.72
< $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
$2.05
< $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
$2.31
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

تفاصيل التسعير

السعر المُوصى به من openrouter · qwen/qwen3-235b-a22b-07-25

$0.150
إدخال
$0.850
إخراج

متاح لدى 1 مزود

المزودمعرف نموذج المزودإدخال / 1Mإخراج / 1Mالسياقتاريخ الإصدار
OpenRouter
openrouter
qwen/qwen3-235b-a22b-07-25$0.150$0.850262K2025-04-28

Frequently asked questions

How much does Qwen3 235B A22B Instruct 2507 cost?

Qwen3 235B A22B Instruct 2507 costs $0.150 per 1M input tokens and $0.850 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 Qwen3 235B A22B Instruct 2507?

Qwen3 235B A22B Instruct 2507 has a context window of 262K tokens, with a max output of 131K tokens per reply. This is the total combined size of prompt + completion.

Does Qwen3 235B A22B Instruct 2507 support tool calling?

Yes. Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507 support structured output / JSON mode?

Yes. Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507 accept image input?

No. Qwen3 235B A22B Instruct 2507 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Qwen3 235B A22B Instruct 2507 open-weight?

Yes. Qwen3 235B A22B Instruct 2507'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 235B A22B Instruct 2507?

If Qwen3 235B A22B Instruct 2507 doesn't fit, consider LFM2.5-1.2B-Instruct (free), LFM2.5-1.2B-Thinking (free), Owl Alpha. 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 come from the public models.dev API and are normalised into a single canonical model record. 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

آخر تحديث:

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.