Tencent: Hunyuan A13B Instruct vs Google: Nano Banana (Gemini 2.5 Flash Image): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Tencent: Hunyuan A13B Instruct (tencent/hunyuan-a13b-instruct) vs Google: Nano Banana (Gemini 2.5 Flash Image) (google/gemini-2.5-flash-image). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Tencent: Hunyuan A13B Instruct (tencent/hunyuan-a13b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Tencent: Hunyuan A13B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.07/1M) or route via asynchronous Batch API for 50% off standard token rates.
Google: Nano Banana (Gemini 2.5 Flash Image) (google/gemini-2.5-flash-image) — 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 Tencent: Hunyuan A13B Instruct (API ID: tencent/hunyuan-a13b-instruct) vs Google: Nano Banana (Gemini 2.5 Flash Image) (API ID: google/gemini-2.5-flash-image), Tencent: Hunyuan A13B Instruct offers lower standard input pricing at $0.14/1M tokens ($0.57/1M output), while Tencent: Hunyuan A13B Instruct leads in cached prefix economics at $0.07/1M tokens (50% discount). Tencent: Hunyuan A13B Instruct 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 | Tencent: Hunyuan A13B Instruct | Google: Nano Banana (Gemini 2.5 Flash Image) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | tencent/hunyuan-a13b-instruct | google/gemini-2.5-flash-image | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.14 / $0.57 | $0.3 / $2.5 | Tencent: Hunyuan A13B Instruct |
| Cache Read Price (per 1M) | $0.07/1M (50% Off) | $0.15/1M (50% Off) | Tencent: Hunyuan A13B Instruct |
| Context Window / Max Output | 128K In / 115K Out | 32K In / 8K Out | Tencent: Hunyuan A13B Instruct |
| P90 First-Token / Edge Latency | 280ms | 280ms | Tencent: Hunyuan A13B Instruct (-0ms) |
Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thou
Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image gene
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 Tencent: Hunyuan A13B Instruct to Google: Nano Banana (Gemini 2.5 Flash Image)
Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image gene Verified P90 latency of 280ms.