OpenAI: gpt-oss-120b vs Google: Gemma 4 26B A4B : Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing OpenAI: gpt-oss-120b (openai/gpt-oss-120b) vs Google: Gemma 4 26B A4B (google/gemma-4-26b-a4b-it). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
OpenAI: gpt-oss-120b (openai/gpt-oss-120b) 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).
Google: Gemma 4 26B A4B (google/gemma-4-26b-a4b-it) — 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.
In Etuki October 2026 FinOps telemetry comparing OpenAI: gpt-oss-120b (API ID: openai/gpt-oss-120b) vs Google: Gemma 4 26B A4B (API ID: google/gemma-4-26b-a4b-it), Google: Gemma 4 26B A4B offers lower standard input pricing at $0.09/1M tokens ($0.3/1M output), while Google: Gemma 4 26B A4B leads in cached prefix economics at $0.045/1M tokens (50% discount). OpenAI: gpt-oss-120b achieves a 0ms faster P90 time-to-first-token latency (280ms vs 280ms).
Auto-discovered via live global telemetry registry.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | OpenAI: gpt-oss-120b | Google: Gemma 4 26B A4B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | openai/gpt-oss-120b | google/gemma-4-26b-a4b-it | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.15 / $0.6 | $0.09 / $0.3 | Google: Gemma 4 26B A4B |
| Cache Read Price (per 1M) | $0.075/1M (50% Off) | $0.045/1M (50% Off) | Google: Gemma 4 26B A4B |
| Context Window / Max Output | 128K In / 64K Out | 256K In / 230K Out | Google: Gemma 4 26B A4B |
| P90 First-Token / Edge Latency | 280ms | 280ms | OpenAI: gpt-oss-120b (-0ms) |
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. I
Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — deli
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 OpenAI: gpt-oss-120b to Google: Gemma 4 26B A4B
Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — deli Verified P90 latency of 280ms.