ModelRefs / Text Embedding 3 Large vs Qwen 2.5 Coder 32B
Text Embedding 3 Large vs Qwen 2.5 Coder 32B
Text Embedding 3 Large vs Qwen 2.5 Coder 32B: side-by-side benchmarks, pricing, context windows, coding ability and deployment. Pick the right model for your…
Overview
Qwen 2.5 Coder 32B: Qwen 2.5 Coder 32B Instruct is Alibaba's code-specialised model, 32.5 billion parameters (31.0 billion excluding embeddings) trained on 5.5 trillion tokens of source code, text-code grounding and synthetic data, and released under Apache 2.0. Qwen builds it for code generation, code reasoning and code repair. The published config sets a 32,768-token context by default; reaching the full 131,072 tokens requires YaRN scaling, which Qwen notes can degrade quality on shorter inputs.
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: Qwen 2.5 Coder 32B accepts up to 131,072 tokens, Text Embedding 3 Large up to 8,191. Confirm the limit for your specific deployment channel before relying on it.
Qwen 2.5 Coder 32B vs Text Embedding 3 Large at a glance
| Attribute | Qwen 2.5 Coder 32B | Text Embedding 3 Large |
|---|---|---|
| Provider | Alibaba | OpenAI |
| Released | 2024-11-12 | 2024-01-25 |
| Context window | 131,072 tokens | 8,191 tokens |
| Input price | $0.18/M tokens | $0.13/M tokens |
| Output price | $0.18/M tokens | Free / self-hosted |
| Licence | Apache-2.0 | Proprietary |
| Self-hostable | Yes, open weights | No, hosted only |
| Modalities | text | text, Embedding |
Where they differ most
- Cost Efficiency: Qwen 2.5 Coder 32B 96%, Text Embedding 3 Large 99%. Text Embedding 3 Large 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 Qwen 2.5 Coder 32B.
Frequently asked questions
Which is better, Text Embedding 3 Large or Qwen 2.5 Coder 32B?
Text Embedding 3 Large and Qwen 2.5 Coder 32B target different workloads — see the benchmark and pricing tables for a side-by-side answer.
Is Text Embedding 3 Large cheaper than Qwen 2.5 Coder 32B?
Compare $0.00013 vs $0.00018 on this page.