Cohere

Cohere — Enterprise-focused models built for RAG and private deployment. Cohere sells to regulated enterprises: the Command family plus best-in-class rerank and embedding models, deployable into your own VPC or on-premise rather than only as a hosted endpoint. It has largely stopped competing on frontier benchmarks and instead competes on retrieval quality, deployment flexibility and contractual terms — which is a defensible position with a narrow audience. Founded 2019. Late-stage private. Licensed CC-BY-NC (research weights).

We track it in 1 comparison — LLM APIs — so every claim below is a cell in a table you can open and check rather than an impression. Across those rosters it sits against 17 other tools, and what follows is where it visibly separates from them.

Where it wins.

• API since — 2021, 2nd of 18.

Each of those is ranked against the whole roster on its category page, not against a hand-picked subset, so a first place here means first of everything we list.

Where it gives ground.

• Context window — 256,000 tokens, 7th of 10. Anthropic records 1,000,000 tokens.
• Effort control — No. Anthropic records Yes.

None of these disqualify it on their own. They are the fields to check against your own requirements before you commit, because they are the ones where a competitor genuinely does better.

Provenance. 20 of 27 tracked fields carry a value for Cohere, and 3 of those cite a document you can open. Last verified 2026-01-15. Every figure keeps its own provenance — measured by us, claimed by the vendor, inferred, or community-reported — and we would rather print a dash than a guess.

Its nearest neighbour in our data is Qwen. Cohere is ahead on Schema output (Yes against Partial) and API since (2021 against 2023). Qwen takes Trains on your data (Partial against No) and Effort control (Partial against No). That pattern repeats across the rest of the roster — see Cohere alternatives for the other rivals, each compared the same way.

Founded

2019

Funding

Late-stage private

Licence

CC-BY-NC (research weights)

Fields we track

20 of 27

Last verified

2026-01-15

Has sensibly stopped chasing the frontier and now competes where it can win: retrieval quality, private deployment and enterprise contracts. Its rerank and embedding models remain best-in-class and are the more common reason to be a customer. As a general-purpose chat API it is priced like a frontier lab without matching one.

$/M output

$10 /M tok5th of 8

Inferredverified 2026-01-15

Context window

256,000 tokens7th of 10

Inferredverified 2026-01-15

$/M input

$2.5 /M tok7th of 8

Inferredverified 2026-01-15source

Tool use

●Yes1st of 18

Vendor-claimedverified 2026-01-15source

Schema output

●Yes1st of 18

Inferredverified 2026-01-15

Pinnable versions

●Yes1st of 18

Vendor-claimedverified 2026-01-15source

Trains on your data

○No7th of 18

Inferredverified 2026-01-15

Effort control

○No12th of 18

Inferredverified 2026-01-15

Cohere is the right call in these situations, each one drawn from a field we actually record:

• RAG pipelines where rerank quality drives the result.
• Deployments that must run inside your own VPC or data centre.
• Enterprises whose procurement needs a vendor agreement, not a credit card.
• API since is your binding constraint. Cohere records 2021, 2nd of 18 in the LLM APIs roster. We define that field as year the provider first made a general-availability inference API public, as a rough proxy for operational maturity.

Reach for something else when any of the following is a requirement rather than a nice-to-have:

• Context window. Cohere records 256,000 tokens, 7th of 10 in the LLM APIs roster. Anthropic records 1,000,000 tokens on the same field. If that is a hard requirement rather than a preference, start elsewhere.
• Effort control. Cohere records No on the LLM APIs table. Anthropic records Yes on the same field. If that is a hard requirement rather than a preference, start elsewhere.

We publish this block because a comparison that only lists what a tool is good at is marketing. Every figure above sits on the same page as its source, and the field definitions are on the category tables if you want to check how we measured them.

What we don't know. 7 of the 27 fields we track for Cohere are still blank: Max output, TTFT p50, Output tok/s, $/M cache read, Batch discount, Cache TTL and Notice period. Those render as dashes rather than as zeroes or assumptions, because an empty cell and a bad cell are not the same thing and only one of them is honest. If you know any of these figures and can point at a document, tell us.