Simulating realistic Data extraction & tagging parameters (2,000 in / 250 out with 20% cache reuse). Together AI — DeepSeek V4 delivers a 45% cost reduction over GLM-5 (Z.ai).
| Traffic Volume Tier | Together AI — DeepSeek V4 Monthly | GLM-5 (Z.ai) Monthly | Monthly Savings by picking Together AI — DeepSeek V4 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $1.375 | $2.48 | Save $1.105 / mo |
| 10,000 reqs/mo (Small App) | $13.75 | $24.80 | Save $11.05 / mo |
| 100,000 reqs/mo (Growth Production) | $137.50 | $248.00 | Save $110.50 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $1,375.00 | $2,480.00 | Save $1,105.00 / mo |
Together AI — DeepSeek V4 is 45% cheaper for Data extraction & tagging workloads. At standard Data extraction & tagging parameter ratios (2,000 input tokens, 250 output tokens, 20% cache hit), Together AI — DeepSeek V4 costs $0.001375 per request compared to $0.00248 on GLM-5 (Z.ai).
Together AI — DeepSeek V4 offers a context window of 1,000,000 tokens (max output: 64,000), while GLM-5 (Z.ai) offers 200,000 tokens (max output: 131,072).
At 100,000 requests per month, using Together AI — DeepSeek V4 saves $110.50 every month (or $1,326.00 annually) compared to GLM-5 (Z.ai).
Volume makes nano-tier models attractive — extraction rarely needs frontier reasoning. Constrain output with JSON schema modes to avoid retry loops on malformed responses. Cache shared schema instructions and few-shot examples across calls.