Sakana: Fugu Max vs Google: Gemini 4 Argon (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Sakana: Fugu Max (sakana/fugu-max) vs Google: Gemini 4 Argon (batch) (google/gemini-4-argon:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Sakana: Fugu Max (sakana/fugu-max) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Sakana: Fugu Max: Activate ephemeral prefix caching to slash input costs by 50% (down to $1/1M) or route via asynchronous Batch API for 50% off standard token rates.
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.
In Etuki October 2026 FinOps telemetry comparing Sakana: Fugu Max (API ID: sakana/fugu-max) vs Google: Gemini 4 Argon (batch) (API ID: google/gemini-4-argon: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). Sakana: Fugu Max 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 | Sakana: Fugu Max | Google: Gemini 4 Argon (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | sakana/fugu-max | google/gemini-4-argon:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $2 / $6 | $1 / $5 | Google: Gemini 4 Argon (batch) |
| Cache Read Price (per 1M) | $1/1M (50% Off) | $0.5/1M (50% Off) | Google: Gemini 4 Argon (batch) |
| Context Window / Max Output | 977K In / 125K Out | 1024K In / 922K Out | Google: Gemini 4 Argon (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Sakana: Fugu Max (-0ms) |
Fugu Max is the cost-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model train
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
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 Sakana: Fugu Max to Google: Gemini 4 Argon (batch)
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 Verified P90 latency of 280ms.