Reflection: Beam 1.0 501B A23B vs inclusionAI: Ling 3.0 Flash VL: Live Promos, Pricing, Hidden Fees & Latency
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 $0.5/1M) or route via asynchronous Batch API for 50% off standard token rates.
inclusionAI: Ling 3.0 Flash VL (inclusionai/ling-3.0-flash-vl) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for inclusionAI: Ling 3.0 Flash VL: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.03/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Reflection: Beam 1.0 501B A23B (API ID: reflection/beam-1.0-501b-a23b) vs inclusionAI: Ling 3.0 Flash VL (API ID: inclusionai/ling-3.0-flash-vl), inclusionAI: Ling 3.0 Flash VL offers lower standard input pricing at $0.06/1M tokens ($0.18/1M output), while inclusionAI: Ling 3.0 Flash VL leads in cached prefix economics at $0.03/1M tokens (50% discount). Reflection: Beam 1.0 501B A23B 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 | Reflection: Beam 1.0 501B A23B | inclusionAI: Ling 3.0 Flash VL | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | reflection/beam-1.0-501b-a23b | inclusionai/ling-3.0-flash-vl | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $3 | $0.06 / $0.18 | inclusionAI: Ling 3.0 Flash VL |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $0.03/1M (50% Off) | inclusionAI: Ling 3.0 Flash VL |
| Context Window / Max Output | 1024K In / 922K Out | 128K In / 32K Out | Reflection: Beam 1.0 501B A23B |
| P90 First-Token / Edge Latency | 280ms | 280ms | Reflection: Beam 1.0 501B A23B (-0ms) |
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
Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception an
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 Reflection: Beam 1.0 501B A23B to inclusionAI: Ling 3.0 Flash VL
Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception an Verified P90 latency of 280ms.