identity

open weights
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Qwen/Qwen3-32B:flexDeepInfra Inc.

in /1M$0.06input tokens
out /1M$0.22output tokens
context41Ktokens
trainingnoon your prompts
api
chat
hosting
US
model lab
Alibaba (Qwen)
weights
open
added
April 2025
model id
deepinfra/Qwen/Qwen3-32B:flex

capabilities 1/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

2 providers serve qwen3-32b. This page is one of them. Compare all endpoints

pricing

no markup
input
$0.06
output
$0.22
cache write
-
cache read
-

worked cost

Estimated cost for three request volumes
volumecost
100K in + 10K out$0.0086
1M in + 100K out$0.0864
10M in + 1M out$0.86

Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing

provider price, passed throughper 1M tokens

measured

through Sep 12

no measured traffic for this endpoint yet. pricing above is the provider's own

benchmarks

artificial analysis
Benchmark scores, each normalised to 100
evalScore as a share of 100/100
MMLU Pro72.7
GPQA Diamond53.5
LiveCodeBench28.8
Math Index19.7
AIME 202519.7
Intelligence Index7.3
Humanity's Last Exam4.1
7 evalsmean29.4

Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2025-04-28.

policy

data terms
retention
none
trains on prompts
no
hosted in
US

Terms are the provider's, not Requesty's: routing a request here puts it under them. DeepInfra Privacy Policy

Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.

quickstart

openai compatible
deepinfra/Qwen/Qwen3-32B:flex

this id pins the deepinfra inc. deployment, with no routing and no failover. the managed id on the canonical page routes across all 2 providers instead

main.py
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="deepinfra/Qwen/Qwen3-32B:flex",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models

notes

reference

Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique ability to switch seamlessly between a thinking mode for complex reasoning and a non-thinking mode for efficient dialogue ensures versatile, high-quality performance. Significantly outperforming prior models like QwQ and Qwen2.5, Qwen3 delivers superior mathematics, coding, commonsense reasoning, creative writing, and interactive dialogue capabilities. The Qwen3-30B-A3B variant includes 30.5 billion parameters (3.3 billion activated), 48 layers, 128 experts (8 activated per task), and supports up to 131K token contexts with YaRN, setting a new standard among open-source models.

questions 6

How much does Qwen/Qwen3-32B:flex cost?
Qwen/Qwen3-32B:flex is priced at $0.06 per million input tokens and $0.22 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of Qwen/Qwen3-32B:flex?
Qwen/Qwen3-32B:flex has a context window of 41K tokens. That is roughly 55 words of input you can fit in a single prompt.
How does Qwen/Qwen3-32B:flex perform on benchmarks?
Qwen/Qwen3-32B:flex scores 72.7% on MMLU Pro, 53.5% on GPQA Diamond, 28.8% on LiveCodeBench. The benchmarks pane shows every published result, each normalised to 100.
What can Qwen/Qwen3-32B:flex do?
Qwen/Qwen3-32B:flex supports tool calling. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use Qwen/Qwen3-32B:flex 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 "deepinfra/Qwen/Qwen3-32B:flex". The quickstart pane shows Python, JavaScript and cURL snippets.
Can I run Qwen/Qwen3-32B:flex through Requesty?
Yes. Qwen/Qwen3-32B:flex runs through Requesty's OpenAI-compatible API, served from DeepInfra Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/Qwen/Qwen3-32B:flex", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

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call qwen/qwen3-32b:flex through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover when a provider degrades, and prompt caching built in. Methodology

Qwen/Qwen3-32B:flexdeepinfra inc.in $0.06 /1Mout $0.22 /1Mctx 41Khosted US2 providers serve this model