Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). GLM-5.1 (Z.ai) delivers a 49% cost reduction over Cohere Command A+.
| Traffic Volume Tier | Cohere Command A+ Monthly | GLM-5.1 (Z.ai) Monthly | Monthly Savings by picking GLM-5.1 (Z.ai) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $33.80 | $17.392 | Save $16.408 / mo |
| 10,000 reqs/mo (Small App) | $338.00 | $173.92 | Save $164.08 / mo |
| 100,000 reqs/mo (Growth Production) | $3,380.00 | $1,739.20 | Save $1,640.80 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $33,800.00 | $17,392.00 | Save $16,408.00 / mo |
GLM-5.1 (Z.ai) is 49% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), GLM-5.1 (Z.ai) costs $0.0174 per request compared to $0.0338 on Cohere Command A+.
Cohere Command A+ offers a context window of 128,000 tokens (max output: 8,192), while GLM-5.1 (Z.ai) offers 200,000 tokens (max output: 131,072).
At 100,000 requests per month, using GLM-5.1 (Z.ai) saves $1,640.80 every month (or $19,689.60 annually) compared to Cohere Command A+.
Output is the expensive side — prefer models with cheap output for autocomplete-style calls. Cache repository context between keystrokes; diffs change far less than the full file. Measure acceptance rate: paying for output users delete is pure waste.