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qwen/qwen-2.5-72b-instruct

Novita AI/🇺🇸 US/chat

Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters.More

Which id to call

novita/qwen/qwen-2.5-72b-instruct

This exact deployment on Novita AI, with no routing and no failover. Send it as the model field.

Input /1M

$0.38

Novita AI

Output /1M

$0.40

1.1x input

Context

32K

tokens

Added

Sep 2024

chat

Capabilities 1/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What qwen/qwen-2.5-72b-instruct costs

Provider prices per 1M tokens, updated September 8, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$0.38

Output /1M

$0.40

Cache write /1M

-

Cache read /1M

-

What a workload costs

100K input + 10K output
$0.0420
1M input + 100K output
$0.42
10M input + 1M output
$4.20

At the rates above. This endpoint does not offer prompt caching, so repeated context is billed as new input every time.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to novita/qwen/qwen-2.5-72b-instruct. Existing OpenAI SDK code needs no other edit.

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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="novita/qwen/qwen-2.5-72b-instruct", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window32K tokens
Max output-
API typechat
AddedSep 2024
Model id
Data retentionNone
Used for trainingNo
Served from🇺🇸 US

Public leaderboards

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

No benchmarks are published for this exact variant yet.

Region-specific deployments and highspeed tiers usually share scores with their base model. Try the base model page or the Novita AI models overview.

Same provider

More from Novita AI

Newest first, on the same provider and the same key.

Reference

qwen/qwen-2.5-72b-instruct questions

How much does qwen/qwen-2.5-72b-instruct cost?

qwen/qwen-2.5-72b-instruct is priced at $0.38 per million input tokens and $0.40 per million output tokens when accessed via Requesty. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of qwen/qwen-2.5-72b-instruct?

qwen/qwen-2.5-72b-instruct has a context window of 32K tokens. That's roughly 43 words of input you can fit in a single prompt.

What can qwen/qwen-2.5-72b-instruct do?

qwen/qwen-2.5-72b-instruct supports tool calling. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use qwen/qwen-2.5-72b-instruct 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 "novita/qwen/qwen-2.5-72b-instruct". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run qwen/qwen-2.5-72b-instruct through Requesty?

Yes. qwen/qwen-2.5-72b-instruct runs through Requesty's OpenAI-compatible API, served from Novita AI. You do not host the model yourself: point base_url at Requesty, set the model to "novita/qwen/qwen-2.5-72b-instruct", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call qwen/qwen-2.5-72b-instruct through one endpoint

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

All Novita AI models