Qwen · Open weights

Qwen2.5 VL 72B TEE

Added Jan 1, 2024Open weights

Qwen2.5 Vision-Language 72B model with multimodal capabilities. Running inside a TEE (Trusted Execution Environment), with provider attestation support.

Vision

Input: Text, Images
Output: Text
Discovery tier: Open weights

Pricing

USD per 1M tokens

Input: $0.70
Output: $0.70

Reference prices as published by the model provider. API example

Specifications

Context window: 65.5K
Max output: 8.2K
Average output (7 days): 84 tokens; Longer than 8% of 468 models

Side by side

Qwen2.5 VL 72B TEE compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

Limits
	Qwen2.5 VL 72B TEEQwenThis model	Llama 3.3 70B Instruct abliteratedMetaRemove
Provider	Qwen	Meta
Discovery tier	Open weights	Open weights
Added	Jan 1, 2024	Aug 8, 2025
Context window	65.54KBest	32.77K
Max output	8.19K	—
Average output	84 tokens	129 tokens
Pricing, USD per 1M tokens
Input	$0.70	$0.70
Output	$0.70	$0.70
Performance
Request success (24h)	—	20.8%
Capabilities
Vision	Yes	No
Reasoning effort	—	—

Public evaluations

Benchmarks

There are no public benchmark results for these models yet.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart

curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "TEE/qwen2.5-vl-72b-instruct",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="TEE/qwen2.5-vl-72b-instruct",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.