OpenAI vs Cohere vs Voyage: Which Embedding Model to Choose
Use OpenAI text-embedding-3 (large or small) for general-purpose production retrieval: strong quality, well-supported, reasonable cost, the default choice for most BearPlex engagements. Use Cohere Embed v3 for multilingual workloads or when you want native reranking integration. Use Voyage AI for domain-specific work where their domain-tuned models (voyage-code, voyage-finance, voyage-law) outperform general-purpose models. Use open-source (BGE, E5) for self-hosted requirements. Quality differences between top embedding models on most production tasks are 1-5%: choose based on operational fit (cost, multilingual, sovereignty) rather than chasing benchmark differences.
Side-by-side comparison
| Dimension | OpenAI text-embedding-3 | Cohere Embed v3 |
|---|---|---|
| License | Closed source SaaS | Closed source SaaS |
| Quality (general) | Strong | Strong |
| Multilingual | Limited (English-primary) | Strong (100+ languages) |
| Domain-specific variants | No | No |
| Reranking integration | Generic (any reranker) | Native Cohere Rerank |
| Dimensions | 1536 / 3072 (Matryoshka truncatable) | 1024 (also Light variant 384) |
| Cost (per 1M tokens) | $0.02-$0.13 | $0.10 |
| Enterprise availability | Azure OpenAI | AWS Bedrock |
| Best for | General-purpose, English-primary | Multilingual, with reranking |
OpenAI text-embedding-3
Strong general-purpose embeddings, well-supported. The production default.
OpenAI text-embedding-3-large (3072 dims) and text-embedding-3-small (1536 dims) are widely-used production embedding models. Strong quality on general benchmarks; well-supported with extensive ecosystem; reasonable cost; Matryoshka training enables flexible dimension reduction. The default choice for most BearPlex production engagements unless specific requirements (multilingual, domain-specific, sovereignty) point elsewhere.
Pros
- Strong quality on general benchmarks
- Well-supported with extensive ecosystem
- Matryoshka training enables flexible dimensions
- Reasonable cost
- OpenAI platform integration
- Widely tested in production
Cons
- Limited multilingual coverage compared to Cohere
- No domain-specific variants
- Closed source
- Vendor lock-in to OpenAI
Best for
- → General-purpose production retrieval
- → Teams already on OpenAI platform
- → English-primary workloads
Worst for
- → Multilingual workloads (Cohere stronger)
- → Domain-specific work (Voyage stronger)
- → Self-hosted requirements (open-source needed)
$0.13 per 1M tokens (large), $0.02 per 1M tokens (small).
Hours from sign-up to first embedding.
Cohere Embed v3
Strong multilingual embeddings. Native reranking integration.
Cohere Embed v3 provides strong production embeddings with excellent multilingual support (100+ languages) and dedicated reranking integration via Cohere Rerank. Strong choice for multilingual workloads or when reranking is part of the retrieval pipeline. Closed-source SaaS (with private deployment options for enterprise).
Pros
- Excellent multilingual support (100+ languages)
- Native Cohere Rerank integration
- Strong production track record
- Available on AWS Bedrock for enterprise
- Strong embeddings for English plus other languages
Cons
- Closed source
- Smaller ecosystem than OpenAI
- Per-token cost similar to OpenAI
- No domain-specific variants
Best for
- → Multilingual production retrieval
- → Pipelines using Cohere Rerank
- → Global SaaS with international customer bases
Worst for
- → English-only workloads where OpenAI is sufficient
- → Domain-specific retrieval (Voyage stronger)
- → Self-hosted requirements
$0.10 per 1M tokens.
Hours from sign-up to first embedding.
Decision scenarios
Production RAG for English-language B2B SaaS
OpenAI text-embedding-3. Strong quality, well-supported, reasonable cost. Default choice.
Multilingual customer support across 12 languages
Cohere Embed v3 multilingual. Quality across 12 languages; pairs well with Cohere Rerank for hybrid retrieval.
Code search across large codebases
Voyage AI voyage-code is the third option here: domain-tuned for code. Worth benchmarking against OpenAI / Cohere on the specific task.
Healthcare client requiring HIPAA-compliant embeddings
Both via enterprise platforms (Azure OpenAI for OpenAI, AWS Bedrock for Cohere) with HIPAA BAA. Sovereign self-hosted (open-source BGE) is the third option.
Healthcare RAG over clinical documents in English
OpenAI text-embedding-3 (or Voyage's healthcare variants if available). Strong general-purpose quality on English clinical content.
Self-hosted requirement for sovereignty
Neither: open-source BGE (BAAI), E5 (Microsoft), or GTE (Alibaba) for self-hosted requirements.
Common questions
Voyage AI is a third major embedding provider with strong domain-tuned variants (voyage-code, voyage-finance, voyage-law). Generally competitive with OpenAI / Cohere on general tasks; often better on in-domain tasks. Worth benchmarking for specialized work.
BGE (BAAI), E5 (Microsoft), GTE (Alibaba), nomic-embed are strong open-source options. Performance approaching managed alternatives on most tasks. Choose for self-hosted / sovereignty requirements or aggressive cost optimization.
Sometimes. Re-embedding 10M documents with OpenAI text-embedding-3-large costs ~$200-500, not prohibitive. A/B test retrieval quality on your eval set before migrating. We migrate clients periodically when quality improvements justify the work.
1536 (OpenAI text-embedding-3-small or text-embedding-3-large truncated) is a strong default. 3072 (text-embedding-3-large full) for highest quality. 384-768 from open-source for cost optimization. Always tune empirically; don't guess.
Voyage AI provides domain-specific variants. They typically outperform general-purpose embeddings on in-domain tasks by 5-15%. Worth using when the workload is heavily concentrated in one domain.
We benchmark on the specific data and use case. Default starting point is OpenAI text-embedding-3 unless requirements (multilingual, domain, sovereignty) point elsewhere. We don't religiously prefer any provider.
Related comparisons
Related services
Featured case studies
Get a recommendation tailored to your situation
BearPlex builds production AI systems using both approaches. We'll tell you which fits your case in a 30-minute scoping call.