ModelRefs / Text Embedding 3 Large vs Phi-4 — Benchmarks, Pricing & Cod…

Text Embedding 3 Large vs Phi-4 — Benchmarks, Pricing & Cod…

Text Embedding 3 Large vs Phi-4: side-by-side benchmarks, pricing, context windows, coding ability and deployment. Pick the right model for your stack.

Overview

Phi-4: Microsoft's 14B dense decoder-only open-weight text model, trained on 9.8T tokens with a synthetic-data-centered curriculum and available through the microsoft/phi-4 artifact and Microsoft Foundry.

Context window: Phi-4 accepts up to 16,384 tokens, Text Embedding 3 Large up to 8,191. Confirm the limit for your specific deployment channel before relying on it.

Phi-4 vs Text Embedding 3 Large at a glance

AttributePhi-4Text Embedding 3 Large
ProviderMicrosoftOpenAI
Released2024-12-122024-01-25
Context window16,384 tokens8,191 tokens
Input priceFree / self-hosted$0.13/M tokens
Output priceFree / self-hostedFree / self-hosted
LicenceMITProprietary
Self-hostableYes, open weightsNo, hosted only
Modalitiestexttext, Embedding

Where they differ most

  • Multilingual: Phi-4 81%, Text Embedding 3 Large 78%. Phi-4 leads on this dimension.
  • Cost Efficiency: Phi-4 100%, Text Embedding 3 Large 99%. Phi-4 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 Phi-4 — Benchmarks, Pricing & Cod….

Frequently asked questions

Which is better, Text Embedding 3 Large or Phi-4?

Text Embedding 3 Large and Phi-4 target different workloads — see the benchmark and pricing tables for a side-by-side answer.

Is Text Embedding 3 Large cheaper than Phi-4?

Compare $0.00013 vs $0.00000 on this page.