Nomic Embed vs Cohere Embed 4
Both are alternatives to OpenAI Embeddings API. Here's how they stack up — verified facts, no spin.
Also searched as Cohere Embed 4 vs Nomic Embed — same comparison, one verdict.
Nomic Embed is open source (Apache-2.0) and Cohere Embed 4 is not (Proprietary hosted service) — so the real question is whether you want to own the embedding models stack or rent it.
Nomic Embed
TOP PICKThe sovereign default — Apache-2.0, one command in Ollama, up to 8k context with rotary scaling.
nomic-embed-text-v1.5 is the open model that made local embeddings boring: Apache-2.0 with the training recipe published, Matryoshka dimensions to trade size for speed, and one-command serving through Ollama on hardware you already own. Its context is 2,048 tokens by default and scales to 8,192 with dynamic rotary scaling switched on — Ollama's build stops at 2K, so chunk to fit.
Cohere Embed 4
The enterprise multilingual option with a 128k context.
Cohere's Embed 4 reads whole documents at once (128,000-token context), specializes in multilingual retrieval, and — unusually for hosted AI — deploys into AWS, Azure, or your own VPC for compliance-bound enterprises. $0.12 per million tokens.
Side by side
10 points of comparison, every one read from a verified field. Green marks the side that wins a row outright. A dash means we do not hold that fact — never that it is zero.
| Nomic Embed | Cohere Embed 4 | |
|---|---|---|
| Sovereignty ScoreOur transparent 0–100 composite for data ownership and exit cost. | 92 | 36 |
| Open source | Yes | No |
| Self-hostable | Yes | No |
| Local-first data | Yes | No |
| License | Apache-2.0 | Proprietary hosted service |
| Pricing | Free — runs locally via Ollama or sentence-transformers; your hardware is the cost | $0.12/1M tokens; private-deployment options for enterprise |
| RAM to run it wellThe figure that actually matters, not the vendor's minimum. | Around 1 GB of RAM or VRAM for one request at a time (estimate from the 274–547 MB weights; no figure is published). Batching long inputs raises it. | — |
| Realistic running costWhat the box costs each month if you run it yourself. | $0 — it runs on the machine you already own | — |
| Setup timeHonest first-install estimate, not the marketing quickstart. | 5 minutes with ollama pull; 15 with sentence-transformers | — |
| Ongoing maintenanceThe part nobody budgets for. | Almost none for the model itself. The work is re-embedding: switching version (v1.5 to v2-moe) or dimension means re-indexing every document, because vectors from different models are not comparable. | — |
Nomic Embed is Macrostack's recommended OpenAI Embeddings API alternative, so it's our pick here.
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Weighing both against staying on OpenAI Embeddings API? Is OpenAI Embeddings API free? What it actually costs →
Nomic Embed
Strengths
- +Truly open: Apache-2.0 including the training recipe
- +Up to 8,192 tokens with rotary scaling — 2,048 by default
- +One-command local serving through Ollama, CPU-friendly
Trade-offs
- −English-focused — the multilingual variant is weaker
- −You own the serving and monitoring
- −Benchmark ceiling sits below the premium hosted models
Cohere Embed 4
Strengths
- +128k-token context — embed entire documents
- +Multilingual strength
- +VPC/private deployment paths for compliance
Trade-offs
- −Six times the price of the small tiers
- −Hosted service with enterprise sales gravity
Which one fits you
The trade-offs above, turned into a decision. Find the line that describes your team.
Choose Nomic Embed
if you want the source and the option to fork it, and you would rather run it on your own hardware, and your data should stay on machines you control.
Choose Cohere Embed 4
if 128k-token context — embed entire documents.
Neither, yet
if both carry a real cost you should weigh first — english-focused — the multilingual variant is weaker, and six times the price of the small tiers. If either of those is a dealbreaker for your team, the shortlist is wrong rather than the choice.
What it takes to run these yourself
Real requirements and honest running costs, not the vendor quickstart.
Nomic Embed vs Cohere Embed 4 — common questions
Is Nomic Embed a better fit than Cohere Embed 4 for embedding models?
It depends on what you are optimising for, and the honest split is this: Nomic Embed scores 92 to Cohere Embed 4's 36 on data ownership and exit cost, so it is the safer choice if you care about being able to leave. Cohere Embed 4 earns its place on a different axis — 128k-token context — embed entire documents. Neither is a wrong answer for every team; the table above is the actual comparison.
What happens if we want to switch later?
Nomic Embed keeps its data local or in open formats, so leaving is an export rather than a negotiation. Cohere Embed 4 keeps your data on its own infrastructure, which is the part to plan for: confirm the export path before you commit, not when you are already trying to leave.
Is Nomic Embed free?
Nomic Embed: Free — runs locally via Ollama or sentence-transformers; your hardware is the cost. The other side of this comparison, Cohere Embed 4, is priced as $0.12/1M tokens; private-deployment options for enterprise. "Free" here means no licence fee — if you self-host it you still pay for the server, and the running cost row above is our honest estimate of that.
Can I self-host Nomic Embed?
Nomic Embed can be self-hosted; Cohere Embed 4 cannot, so it stays on the vendor's infrastructure whatever you do.
Are Nomic Embed and Cohere Embed 4 both alternatives to OpenAI Embeddings API?
Yes — both appear in our OpenAI Embeddings API comparison, which is why they are worth putting side by side. People usually arrive here already having decided to move off OpenAI Embeddings API and now choosing between the two replacements, which is a narrower and much easier question.
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Facts verified 2026-07-19. Licenses and pricing change — spotted something out of date? That's a correction we want.