Reflection: Beam 1.0 501B A23B vs Sakana: Sakana Namazu: 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.
Sakana: Sakana Namazu (sakana/sakana-namazu) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Sakana: Sakana Namazu: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.475/1M) 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 Sakana: Sakana Namazu (API ID: sakana/sakana-namazu), Sakana: Sakana Namazu offers lower standard input pricing at $0.95/1M tokens ($4/1M output), while Sakana: Sakana Namazu leads in cached prefix economics at $0.475/1M 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 | Sakana: Sakana Namazu | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | reflection/beam-1.0-501b-a23b | sakana/sakana-namazu | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $1 / $3 | $0.95 / $4 | Sakana: Sakana Namazu |
| Cache Read Price (per 1M) | $0.5/1M (50% Off) | $0.475/1M (50% Off) | Sakana: Sakana Namazu |
| Context Window / Max Output | 1024K In / 922K Out | 256K In / 64K 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
Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Ja
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 Sakana: Sakana Namazu
Sakana Namazu is a Japanese-specialized reasoning model from Sakana AI, based on Kimi K2.6 with additional training for Japanese language and business contexts. It is suited for Ja Verified P90 latency of 280ms.