ModelRefs / Text Embedding 3 Large vs DeepSeek V3
Text Embedding 3 Large vs DeepSeek V3
Text Embedding 3 Large vs DeepSeek V3: side-by-side benchmarks, pricing, context windows, coding ability and deployment. Pick the right model for your stack.
Overview
DeepSeek V3: DeepSeek V3 is DeepSeek's December 2024 open-weights Mixture-of-Experts model, activating 37 billion of 671 billion total parameters per token across a 128,000-token context window. It ships under the MIT licence with published weights and a technical report, and DeepSeek reports its own evaluation table for the text chat model under an 8,000-token output limit.
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: DeepSeek V3 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.
DeepSeek V3 vs Text Embedding 3 Large at a glance
| Attribute | DeepSeek V3 | Text Embedding 3 Large |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Released | 2024-12-26 | 2024-01-25 |
| Context window | 128,000 tokens | 8,191 tokens |
| Input price | $0.27/M tokens | $0.13/M tokens |
| Output price | $1.1/M tokens | Free / self-hosted |
| Licence | MIT | Proprietary |
| Self-hostable | Yes, open weights | No, hosted only |
| Modalities | text | text, Embedding |
Where they differ most
- Cost Efficiency: DeepSeek V3 85%, 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 DeepSeek V3.
Frequently asked questions
Which is better, Text Embedding 3 Large or DeepSeek V3?
Text Embedding 3 Large and DeepSeek V3 target different workloads — see the benchmark and pricing tables for a side-by-side answer.
Is Text Embedding 3 Large cheaper than DeepSeek V3?
Compare $0.00013 vs $0.00027 on this page.