XingChen: Xing4.0 29B A4B (free) vs Meta: Llama 3.1 8B Instruct: Live Promos, Pricing, Hidden Fees & Latency
XingChen: Xing4.0 29B A4B (free) (xingchen-agi/xing4.0-29b-a4b:free) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for XingChen: Xing4.0 29B A4B (free): Activate ephemeral prefix caching to slash input costs by 50% (down to $0/1M) or route via asynchronous Batch API for 50% off standard token rates.
Meta: Llama 3.1 8B Instruct (meta-llama/llama-3.1-8b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama 3.1 8B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.025/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing XingChen: Xing4.0 29B A4B (free) (API ID: xingchen-agi/xing4.0-29b-a4b:free) vs Meta: Llama 3.1 8B Instruct (API ID: meta-llama/llama-3.1-8b-instruct), XingChen: Xing4.0 29B A4B (free) offers lower standard input pricing at $0/1M tokens ($0/1M output), while XingChen: Xing4.0 29B A4B (free) leads in cached prefix economics at $0/1M tokens (50% discount). XingChen: Xing4.0 29B A4B (free) 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 | XingChen: Xing4.0 29B A4B (free) | Meta: Llama 3.1 8B Instruct | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | xingchen-agi/xing4.0-29b-a4b:free | meta-llama/llama-3.1-8b-instruct | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0 / $0 | $0.05 / $0.08 | XingChen: Xing4.0 29B A4B (free) |
| Cache Read Price (per 1M) | $0/1M (50% Off) | $0.025/1M (50% Off) | XingChen: Xing4.0 29B A4B (free) |
| Context Window / Max Output | 256K In / 230K Out | 128K In / 115K Out | XingChen: Xing4.0 29B A4B (free) |
| P90 First-Token / Edge Latency | 280ms | 280ms | XingChen: Xing4.0 29B A4B (free) (-0ms) |
Xing4.0-29B-A4B is an open-weight mixture-of-experts language model from China Telecom's AI team (TeleAI) and the successor to the TeleChat series. It has 29B total parameters with
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance co
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 XingChen: Xing4.0 29B A4B (free) to Meta: Llama 3.1 8B Instruct
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance co Verified P90 latency of 280ms.