Alternative comparison
DeepSeek vs OpenAI API for cost-sensitive workloads
DeepSeek is often considered by teams looking for lower-cost GPT-style alternatives. GPTokens focuses on making the Chinese LLM side easier to test with OpenAI-compatible requests.
Route shortlist
Benchmark comparison
| Model | Total /100 | Extraction | Instructions | Math | Tools | Fully correct | Tokens | Cost (USD) | CPS ($/100 points) |
|---|---|---|---|---|---|---|---|---|---|
DeepSeek v4 Prodeepseek-v4-pro | 99.00 | 98.33 | 98.67 | 99.00 | 100.00 | 57/60 | 116,757 | $0.145106 | $0.146572 |
BenchLocal V3.2 · Original 27 models: 2 October 2026; three full-suite supplements: 15 October 2026 · 60 tasks per model. Total = mean of the four category scores. The original models retain 45 V3 tasks and 15 revised tool tasks; the three additional model IDs each completed all 60 identical tasks. Near-ceiling scores do not establish general capability; V3 scores are not directly comparable. CPS = Cost per Score; shown as USD per 100 score points: retained execution cost ÷ unrounded total score × 100. Free models are shown at $0. Paid-model costs are historical charges, excluding failed requests and discarded retests.
Decision guide
Recommended route
Use DeepSeek v4 Pro as the first DeepSeek route to test, then compare output quality and total cost per completed task against your existing OpenAI baseline.
What to compare
Do not compare only token price. Compare latency, tool-call reliability, refusal behavior, fallback rate, and cost per solved task.
Migration path
Keep your OpenAI-compatible client and change base URL, API key, and model name for GPTokens tests.
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