Google: Gemini 4 Argon (batch) vs OpenAI: GPT-6.1 Sol Pro (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Google: Gemini 4 Argon (batch) (google/gemini-4-argon:batch) vs OpenAI: GPT-6.1 Sol Pro (batch) (openai/gpt-6.1-sol-pro:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Google: Gemini 4 Argon (batch) (google/gemini-4-argon:batch) — Google AI Startup Credits ($350K) & 50% 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.
OpenAI: GPT-6.1 Sol Pro (batch) (openai/gpt-6.1-sol-pro:batch) Startup Credits & Batch API 50% Off Promo
OpenAI GPT-6.1 Sol ($2/$10 base rate) qualifies for immediate 75% automatic prefix caching ($0.50/1M), 50% off 24-hour Batch API completions ($1/$5), and up to $150,000 in OpenAI/Azure Foundry credits via Microsoft for Startups Founders Hub (no VC funding required for initial tiers).
In Etuki October 2026 FinOps telemetry comparing Google: Gemini 4 Argon (batch) (API ID: google/gemini-4-argon:batch) vs OpenAI: GPT-6.1 Sol Pro (batch) (API ID: openai/gpt-6.1-sol-pro:batch), Google: Gemini 4 Argon (batch) offers lower standard input pricing at $1/1M tokens ($5/1M output), while Google: Gemini 4 Argon (batch) leads in cached prefix economics at $0.5/1M tokens (50% discount). Google: Gemini 4 Argon (batch) achieves a 0ms faster P90 time-to-first-token latency (280ms vs 280ms).
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| Specification / FinOps Dimension | Google: Gemini 4 Argon (batch) | OpenAI: GPT-6.1 Sol Pro (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | google/gemini-4-argon:batch | openai/gpt-6.1-sol-pro:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $5 | $1 / $5 | Google: Gemini 4 Argon (batch) |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $0.5/1M (50% Off) | Google: Gemini 4 Argon (batch) |
| Context Window / Max Output | 1024K In / 922K Out | 1025K In / 125K Out | Google: Gemini 4 Argon (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Google: Gemini 4 Argon (batch) (-0ms) |
Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Goo
GPT-6.1 Sol Pro is the same underlying model as [GPT-6.1 Sol](https://openrouter.ai/openai/gpt-6.1-sol), served with `reasoning.mode` set to `pro` for higher-quality responses on c
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 4 Argon (batch) to OpenAI: GPT-6.1 Sol Pro (batch)
GPT-6.1 Sol Pro is the same underlying model as [GPT-6.1 Sol](https://openrouter.ai/openai/gpt-6.1-sol), served with `reasoning.mode` set to `pro` for higher-quality responses on c Verified P90 latency of 280ms.