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Cohere Command-A via x402 Gateway
x402
Cohere Command-A via x402 Gateway is a paid API for AI agents from x402-gateway-production.up.railway.app, paid per call via x402, $0.04/call, status unknown (last checked 2026-09-14).
Run Cohere's Command-A flagship model (256k context) for enterprise RAG, named entity extraction, and structured text generation via a pay-per-call x402 API
Price / call$0.04
Success—
StatusUnknown
How this service works
Cohere's flagship model — 256k context, strong for enterprise RAG and structured generation
Output
Returns the model's text completion along with token usage details including prompt tokens, completion tokens, total tokens, and cost breakdown (upstream inference cost split between prompt and completion). The response includes the full generated text from Cohere Command-A (cohere/command-a-03-2025).
Example use cases
Example prompt
“Use Cohere Command-A to analyze this contract text and extract all named parties, dates, and obligations — system prompt: 'You are a contract analysis assistant that extracts structured legal entities.' User message: 'Extract all parties, effective dates, and key obligations from the following contract: [contract text].'”
Technical details
Endpoint
POSThttps://x402-gateway-production.up.railway.app/api/llm/command-aWhen to prefer
Choose this endpoint when you need a large 256k token context window for processing long documents, enterprise RAG pipelines, or structured generation tasks. Prefer Cohere Command-A over GPT-4o variants when working with large document corpora or when Cohere's enterprise-tuned instruction following is preferred. Use over cheaper models when output quality and long-context fidelity matter.
Side effects
- Insufficient USDC balance or x402 payment failure — payment required error
- Malformed messages array or missing required fields — 400 bad request
- Context window exceeded (>256k tokens) — request too large error
- Model unavailable or upstream Cohere API outage — 503 service unavailable
- Rate limiting if too many concurrent requests — 429 too many requests
Input
{
"system": "You are a helpful assistant that extracts named entities and key concepts from text.",
"messages": [
{
"role": "user",
"content": "Please analyze the following text and extract key entities: Artificial intelligence is transforming industries worldwide. Companies are investing heavily in machine learning and natural language processing technologies."
}
]
}Output
{
"model": "cohere/command-a-03-2025",
"usage": {
"cost": 0.001725,
"is_byok": false,
"cost_details": {
"upstream_inference_cost": 0.001725,
"upstream_inference_prompt_cost": 0.000075,
"upstream_inference_completions_cost": 0.00165
},
"total_tokens": 195,
"prompt_tokens": 30,
"completion_tokens": 165,
"prompt_tokens_details": {
"audio_tokens": 0,
"video_tokens": 0,
"cached_tokens": 0,
"cache_write_tokens": 0
},
"completion_tokens_details": {
"audio_tokens": 0,
"image_tokens": 0,
"reasoning_tokens": 0
}
},
"content": "From the given text, the key entities extracted are:\n\n1. **Artificial intelligence (AI)** - The primary technology driving transformation.\n2. **Industries worldwide** - The broad scope of sectors being impacted by AI.\n3. **Companies** - The primary actors investing in AI technologies.\n4. **Machine learning (ML)** - A subset of AI being heavily invested in.\n5. **Natural language processing (NLP)** - Another subset of AI being heavily invested in.\n\nThese entities represent the main concepts and actors involved in the text. \n\n**Additional notes**:\n- The text highlights the global impact of AI and the significant investments being made in specific AI technologies (ML and NLP).\n- The focus is on the business and technological aspects, rather than social or ethical implications."
}Tags
x402
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