Google Gemini 2.5 Pro Batch vs Reflection: Beam 1.0 501B A23B: 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.
Reflection: Beam 1.0 501B A23B (reflection/beam-1.0-501b-a23b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Reflection: Beam 1.0 501B A23B: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.15/1M) 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 Reflection: Beam 1.0 501B A23B (API ID: reflection/beam-1.0-501b-a23b), Reflection: Beam 1.0 501B A23B offers lower standard input pricing at $0.3/1M tokens ($1/1M output), while Reflection: Beam 1.0 501B A23B leads in cached prefix economics at $0.15/1M 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 | Reflection: Beam 1.0 501B A23B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | google/gemini-2.5-pro-batch | reflection/beam-1.0-501b-a23b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $5 | $0.3 / $1 | Reflection: Beam 1.0 501B A23B |
| Cache Read Price (per 1M) | $0.25/1M (95% Off) | $0.15/1M (50% Off) | Reflection: Beam 1.0 501B A23B |
| Context Window / Max Output | 1050K In / 128K Out | 1024K In / 922K Out | Reflection: Beam 1.0 501B A23B |
| 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.
Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active
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 Reflection: Beam 1.0 501B A23B
Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active Verified P90 latency of 280ms.