Beam 1.0 501B A23B vs Sakana Namazu compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Sakana Namazu — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
| Spec | Beam 1.0 501B A23B | Sakana Namazu | Winner |
|---|---|---|---|
| Maker | Reflection | Sakana AI | – |
| Type | Open-weight | Proprietary | REBeam 1.0 501B A23B |
| Context window | 1M tokens | 262K tokens | REBeam 1.0 501B A23B |
| Input price | $0.25/M · free self-host | $0.95/M | REBeam 1.0 501B A23B |
| Output price | $1/M · free self-host | $4/M | REBeam 1.0 501B A23B |
| Vision / multimodal | No | Yes | SASakana Namazu |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | REBeam 1.0 501B A23B |
| License | Open weights | Proprietary | REBeam 1.0 501B A23B |
Beam 1.0 501B A23B is ~4.0× cheaper than Sakana Namazu on output tokens ($1 vs $4 per M tokens).
| Capability | Beam 1.0 501B A23B | Sakana Namazu |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✗ | ✓ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✓ | ✗ |
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
| Criterion | Beam 1.0 501B A23B | Sakana Namazu |
|---|---|---|
| Cost-efficiency | 4.5 | 4.0 |
| Context window | 5.0 | 4.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 3.5 | 5.0 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
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 parameters per token, and a...
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 Japanese instruction following,...
Beam 1.0 501B A23B is open-weight and competitive on many tasks, but Sakana Namazu may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Yes. Beam 1.0 501B A23B has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Sakana Namazu is API-only and cannot be self-hosted.
Beam 1.0 501B A23B costs $1/M output vs $4/M for Sakana Namazu — roughly 4x cheaper via API, and free if you self-host.
Choose Beam 1.0 501B A23B if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Sakana Namazu if you want frontier capability through a managed API with zero infrastructure to run.
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