Google Gemini 2.5 Pro Batch vs XingChen: Xing4.0 29B A4B (free): Live Promos, Pricing, Hidden Fees & Latency
Google Gemini 2.5 Pro Batch (google/gemini-2.5-pro-batch) — Google AI Startup Credits ($350K) & 95% Cache Promo
Google DeepMind is currently subsidizing Gemini 4 Argon at 50% off standard rates ($2.00/1M input & $10.00/1M output instead of $4/$20) until November 30, 2026, alongside 95% off Context Caching ($0.10/1M) and up to $350,000 in Google for Startups Cloud/Vertex AI credits.
XingChen: Xing4.0 29B A4B (free) (xingchen-agi/xing4.0-29b-a4b:free) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for XingChen: Xing4.0 29B A4B (free): Activate ephemeral prefix caching to slash input costs by 50% (down to 0/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Google Gemini 2.5 Pro Batch (API ID: google/gemini-2.5-pro-batch) vs XingChen: Xing4.0 29B A4B (free) (API ID: xingchen-agi/xing4.0-29b-a4b:free), XingChen: Xing4.0 29B A4B (free) offers lower standard input pricing at $0/1M tokens ($0/1M output), while XingChen: Xing4.0 29B A4B (free) leads in cached prefix economics at $0/1M tokens (50% discount). Google Gemini 2.5 Pro Batch achieves a 135ms faster P90 time-to-first-token latency (145ms vs 280ms).
Prompts exceeding 200K tokens incur 2x tier pricing unless pinned via Google AI Studio Context Caching (75% off).
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | Google Gemini 2.5 Pro Batch | XingChen: Xing4.0 29B A4B (free) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | google/gemini-2.5-pro-batch | xingchen-agi/xing4.0-29b-a4b:free | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $5 | $0 / $0 | XingChen: Xing4.0 29B A4B (free) |
| Cache Read Price (per 1M) | $0.25/1M (95% Off) | $0/1M (50% Off) | XingChen: Xing4.0 29B A4B (free) |
| Context Window / Max Output | 1050K In / 128K Out | 256K In / 230K Out | XingChen: Xing4.0 29B A4B (free) |
| P90 First-Token / Edge Latency | 145ms | 280ms | Google Gemini 2.5 Pro Batch (-135ms) |
Google Gemini 2.5 Pro Batch is Google DeepMind's native multimodal frontier model supporting up to 2M context tokens and implicit context caching.
Xing4.0-29B-A4B is an open-weight mixture-of-experts language model from China Telecom's AI team (TeleAI) and the successor to the TeleChat series. It has 29B total parameters with
Real-Time Stack Cost & Hidden-Fee Simulator (MAU / Token / Egress / GMV)
Calibrated with Reddit r/FinOps & r/devops telemetry: Includes Context Caching, Bandwidth Egress, and MoR Tax
🛰️Switch from Google Gemini 2.5 Pro Batch to XingChen: Xing4.0 29B A4B (free)
Xing4.0-29B-A4B is an open-weight mixture-of-experts language model from China Telecom's AI team (TeleAI) and the successor to the TeleChat series. It has 29B total parameters with Verified P90 latency of 280ms.