Tencent: Hunyuan A13B Instruct vs OpenAI: GPT-4.1 Nano (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Tencent: Hunyuan A13B Instruct (tencent/hunyuan-a13b-instruct) vs OpenAI: GPT-4.1 Nano (batch) (openai/gpt-4.1-nano:batch). 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.
OpenAI: GPT-4.1 Nano (batch) (openai/gpt-4.1-nano: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 Tencent: Hunyuan A13B Instruct (API ID: tencent/hunyuan-a13b-instruct) vs OpenAI: GPT-4.1 Nano (batch) (API ID: openai/gpt-4.1-nano:batch), OpenAI: GPT-4.1 Nano (batch) offers lower standard input pricing at $0.05/1M tokens ($0.2/1M output), while OpenAI: GPT-4.1 Nano (batch) leads in cached prefix economics at $0.025/1M tokens (50% discount). Tencent: Hunyuan A13B Instruct achieves a 0ms faster P90 time-to-first-token latency (280ms vs 280ms).
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Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | Tencent: Hunyuan A13B Instruct | OpenAI: GPT-4.1 Nano (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | tencent/hunyuan-a13b-instruct | openai/gpt-4.1-nano:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.14 / $0.57 | $0.05 / $0.2 | OpenAI: GPT-4.1 Nano (batch) |
| Cache Read Price (per 1M) | $0.07/1M (50% Off) | $0.025/1M (50% Off) | OpenAI: GPT-4.1 Nano (batch) |
| Context Window / Max Output | 128K In / 115K Out | 1023K In / 32K 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
For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million...
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 OpenAI: GPT-4.1 Nano (batch)
For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million... Verified P90 latency of 280ms.