Cohere via VerticalAPI

Cohere models routed by VerticalAPI

Pass the model ID below as model in any OpenAI-compatible request. New Cohere models are typically supported within 24h of release.

Pricing reflects Cohere's rates — you pay Cohere directly. VerticalAPI adds zero markup on tokens.

5-line Cohere call via VerticalAPI

Drop-in replacement for the OpenAI SDK. Works with the OpenAI Python client, Node, Go, curl — anything that speaks HTTP.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.verticalapi.com/v1",
    api_key="vapi_...",
    default_headers={"X-Provider-Key": "..."}
)

response = client.chat.completions.create(
    model="command-r",  # Cohere
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

What VerticalAPI does and does not do with Cohere

Where Cohere shines

Frequently asked questions

Limitations and trade-offs

• Frontier benchmarks (MMLU, SWE-Bench, MATH) trail GPT-5 and Claude Sonnet 4.5.
• 128K context is smaller than Gemini (2M) and Claude (200K) for very-long-document RAG.
• Smaller developer ecosystem and fewer third-party tools than OpenAI or Anthropic.
• No native multimodal (vision, audio, video) — text-only as of 2026.
• Command R+ pricing matches GPT-4o output cost but with weaker general reasoning quality.

Where Cohere is heading

1. Command R++ or Command 4 generation expected in 2026 with frontier-class quality.
2. Multimodal vision input added to Command family.
3. Expanded private and on-prem deployment options targeting government and finance.
4. Deeper integration with Oracle Cloud and other sovereign clouds.

Related questions

ChatGPT, Perplexity and Gemini usually suggest these next.

• Cohere Command R+ vs GPT-4o for RAG — which is better?
• Is Cohere Embed v3 cheaper than OpenAI text-embedding-3 for multilingual?
• How does Cohere's native citation feature work in production RAG?
• Best Cohere model for non-English chatbots?
• Cohere vs Mistral for enterprise EU-friendly deployment?

All supported LLM providers

Same endpoint, same SDK — just change the model and the BYOK header.