ModelRefs / Text Embedding 3 Large vs Qwen2.5-VL 72B

Text Embedding 3 Large vs Qwen2.5-VL 72B

Text Embedding 3 Large vs Qwen2.5-VL 72B: side-by-side benchmarks, pricing, context windows, coding ability and deployment. Pick the right model for your sta…

Overview

Qwen2.5-VL 72B: Qwen2.5-VL 72B Instruct is the largest vision-language model in Alibaba's Qwen2.5-VL line, accepting images and video alongside text. Qwen highlights comprehension of videos over an hour long, structured extraction from documents such as invoices, forms and tables, visual grounding returned as bounding boxes or points, and agentic computer and phone use. The published config sets a 32,768-token context, and Qwen advises against YaRN extension here because it degrades temporal and spatial localisation.

Text Embedding 3 Large: Text Embedding 3 Large is OpenAI's larger third-generation embedding model, returning 3,072-dimension vectors from inputs of up to 8,192 tokens. Its dimensions parameter shortens the vector at creation time without, as OpenAI puts it, the embedding losing its concept-representing properties, which lets a retrieval system trade index size against accuracy without changing models. Shortening at creation is preferred to truncating afterwards, which requires re-normalising the vector.

Context window: Qwen2.5-VL 72B accepts up to 128,000 tokens, Text Embedding 3 Large up to 8,191. Confirm the limit for your specific deployment channel before relying on it.

Qwen2.5-VL 72B vs Text Embedding 3 Large at a glance

AttributeQwen2.5-VL 72BText Embedding 3 Large
ProviderAlibabaOpenAI
Released2025-01-262024-01-25
Context window128,000 tokens8,191 tokens
Input priceFree / self-hosted$0.13/M tokens
Output priceFree / self-hostedFree / self-hosted
LicenceQwen LicenseProprietary
Self-hostableYes, open weightsNo, hosted only
Modalitiestext, visiontext, Embedding

Where they differ most

  • Cost Efficiency: Qwen2.5-VL 72B 100%, Text Embedding 3 Large 99%. Qwen2.5-VL 72B leads on this dimension.

Capability scores are ModelRefs' own derived signals, not vendor claims or benchmark results. Validate against your own workload before relying on them.

Continue your research

Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Text Embedding 3 Large vs Qwen2.5-VL 72B.

Frequently asked questions

Which is better, Text Embedding 3 Large or Qwen2.5-VL 72B?

Text Embedding 3 Large and Qwen2.5-VL 72B target different workloads — see the benchmark and pricing tables for a side-by-side answer.

Is Text Embedding 3 Large cheaper than Qwen2.5-VL 72B?

Compare $0.00013 vs $0.00000 on this page.