Qwen/Qwen2.5-72B-Instruct
DeepInfra Inc./🇺🇸 US/chat
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.MoreLess
Which id to call
deepinfra/Qwen/Qwen2.5-72B-InstructThis exact deployment on DeepInfra Inc., with no routing and no failover. Send it as the model field.
Input /1M
$0.23
DeepInfra Inc.
Output /1M
$0.40
1.7x input
Context
131K
tokens
Added
Sep 2024
chat
Capabilities 2/8
Provider rates
What Qwen/Qwen2.5-72B-Instruct costs
Provider prices per 1M tokens, updated September 8, 2026.moreless
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
$0.23
Output /1M
$0.40
Cache write /1M
-
Cache read /1M
-
What a workload costs
- 100K input + 10K output
- $0.0270
- 1M input + 100K output
- $0.27
- 10M input + 1M output
- $2.70
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 deepinfra/Qwen/Qwen2.5-72B-Instruct. Existing OpenAI SDK code needs no other edit.
123456789101112131415from 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/Qwen2.5-72B-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.
Released 2024-09-19
Benchmark scores
Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.
Graduate-level physics, chemistry & biology questions designed to resist Googling.
Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.
Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.
Same provider
More from DeepInfra Inc.
Newest first, on the same provider and the same key.
Reference
Qwen/Qwen2.5-72B-Instruct questions
How much does Qwen/Qwen2.5-72B-Instruct cost?
Qwen/Qwen2.5-72B-Instruct is priced at $0.23 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/Qwen2.5-72B-Instruct?
Qwen/Qwen2.5-72B-Instruct has a context window of 131K tokens. That's roughly 175 words of input you can fit in a single prompt.
How does Qwen/Qwen2.5-72B-Instruct perform on benchmarks?
Qwen/Qwen2.5-72B-Instruct scores 72.0% on MMLU Pro, 49.1% on GPQA Diamond, 34.5% on τ²-Bench. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can Qwen/Qwen2.5-72B-Instruct do?
Qwen/Qwen2.5-72B-Instruct supports tool calling, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use Qwen/Qwen2.5-72B-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 "deepinfra/Qwen/Qwen2.5-72B-Instruct". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run Qwen/Qwen2.5-72B-Instruct through Requesty?
Yes. Qwen/Qwen2.5-72B-Instruct 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/Qwen2.5-72B-Instruct", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
Call Qwen/Qwen2.5-72B-Instruct through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.