Meta: Llama 3.3 70B Instruct vs Reflection: Beam 1.0 501B A23B: Live Promos, Pricing, Hidden Fees & Latency
Meta: Llama 3.3 70B Instruct (meta-llama/llama-3.3-70b-instruct) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Meta: Llama 3.3 70B Instruct: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.05/1M) or route via asynchronous Batch API for 50% off standard token rates.
Reflection: Beam 1.0 501B A23B (reflection/beam-1.0-501b-a23b) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Reflection: Beam 1.0 501B A23B: Activate ephemeral prefix caching to slash input costs by 50% (down to 0.15/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Meta: Llama 3.3 70B Instruct (API ID: meta-llama/llama-3.3-70b-instruct) vs Reflection: Beam 1.0 501B A23B (API ID: reflection/beam-1.0-501b-a23b), Meta: Llama 3.3 70B Instruct offers lower standard input pricing at $0.1/1M tokens ($0.32/1M output), while Meta: Llama 3.3 70B Instruct leads in cached prefix economics at $0.05/1M tokens (50% discount). Meta: Llama 3.3 70B 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 | Meta: Llama 3.3 70B Instruct | Reflection: Beam 1.0 501B A23B | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | meta-llama/llama-3.3-70b-instruct | reflection/beam-1.0-501b-a23b | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.1 / $0.32 | $0.3 / $1 | Meta: Llama 3.3 70B Instruct |
| Cache Read Price (per 1M) | $0.05/1M (50% Off) | $0.15/1M (50% Off) | Meta: Llama 3.3 70B Instruct |
| Context Window / Max Output | 128K In / 16K Out | 1024K In / 922K Out | Reflection: Beam 1.0 501B A23B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Meta: Llama 3.3 70B Instruct (-0ms) |
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text on
Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active
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 3.3 70B Instruct to Reflection: Beam 1.0 501B A23B
Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active Verified P90 latency of 280ms.