Model comparison
Qwen3 Max vs Cohere Command A
Compare Qwen3 Max vs Cohere Command A API pricing: input/output token costs, cache pricing, context windows, workload estimates, and routing fit.
Qwen3 Max
novita · novita/qwen/qwen3-max
- Input
- $2.11
- Output
- $8.45
- Context
- 262.1K
Cohere Command A
cohere_chat · command-a-03-2025
- Input
- $2.5
- Output
- $10
- Context
- 256K
Quick take
Qwen3 Max has the lower input price at $2.11 per 1M input tokens. Qwen3 Max is cheaper for the example blended workload below. Qwen3 Max has the larger context window at 262.1K tokens.
Choose Qwen3 Max if...
- Qwen3 Max is the better default for cost-sensitive traffic and repeated high-volume calls.
- Qwen3 Max is safer for long documents, repository analysis, and RAG prompts because it has the larger context window.
- Qwen3 Max gives more room for long generated answers, reports, or code output.
Choose Cohere Command A if...
- Cohere Command A is a reasonable pick when its provider, latency, or integration path fits your stack better.
Example workload cost
Estimates use input tokens plus 20% output tokens. They exclude provider discounts, cache hits, and tool/search surcharges.
| Workload | Qwen3 Max | Cohere Command A | Cheaper |
|---|---|---|---|
| 1M input + 200K output | $3.80 | $4.50 | Qwen3 Max |
| 10M input + 2M output | $38.00 | $45.00 | Qwen3 Max |
| 100M input + 20M output | $380.00 | $450.00 | Qwen3 Max |
Context, output, and capability fit
Qwen3 Max provides the larger context window. Check max output separately when the task needs long reports, code generation, or full-document rewrites.
- Qwen3 Max max output
- 65.5K
- Cohere Command A max output
- 8K
- Qwen3 Max features
- function calling
- Cohere Command A features
- function calling
Risk notes for Qwen3 Max
- No prompt caching in this snapshot: repeated long-context calls may be more expensive.
Risk notes for Cohere Command A
- No prompt caching in this snapshot: repeated long-context calls may be more expensive.
Routing tags
frontiercodingreasoningagentsopen-weightlocal-openenterprise-ragraglong-context