Meta: Llama Guard 4 12B vs OpenAI: gpt-oss-120b (batch): Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Meta: Llama Guard 4 12B (meta-llama/llama-guard-4-12b) vs OpenAI: gpt-oss-120b (batch) (openai/gpt-oss-120b:batch). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Meta: Llama Guard 4 12B (meta-llama/llama-guard-4-12b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama Guard 4 12B: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.09/1M) or route via asynchronous Batch API for 50% off standard token rates.
OpenAI: gpt-oss-120b (batch) (openai/gpt-oss-120b: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 Meta: Llama Guard 4 12B (API ID: meta-llama/llama-guard-4-12b) vs OpenAI: gpt-oss-120b (batch) (API ID: openai/gpt-oss-120b:batch), OpenAI: gpt-oss-120b (batch) offers lower standard input pricing at $0.0296/1M tokens ($0.136/1M output), while OpenAI: gpt-oss-120b (batch) leads in cached prefix economics at $0.0148/1M tokens (50% discount). Meta: Llama Guard 4 12B 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 | Meta: Llama Guard 4 12B | OpenAI: gpt-oss-120b (batch) | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-guard-4-12b | openai/gpt-oss-120b:batch | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.18 / $0.18 | $0.0296 / $0.136 | OpenAI: gpt-oss-120b (batch) |
| Cache Read Price (per 1M) | $0.09/1M (50% Off) | $0.0148/1M (50% Off) | OpenAI: gpt-oss-120b (batch) |
| Context Window / Max Output | 160K In / 16K Out | 128K In / 115K Out | OpenAI: gpt-oss-120b (batch) |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Llama Guard 4 12B (-0ms) |
Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content
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
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 Meta: Llama Guard 4 12B to OpenAI: gpt-oss-120b (batch)
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 Verified P90 latency of 280ms.