gpt-oss-120b (batch) Open vs SASakana Namazu Paid
gpt-oss-120b (batch) 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.
$0.6 /M outputNo per-token fees if you self-host
$4 /M outputManaged API (no infra to run)
gpt-oss-120b (batch) vs Sakana Namazu specs
| Spec | gpt-oss-120b (batch) | Sakana Namazu | Winner |
|---|---|---|---|
| Maker | OpenAI | Sakana AI | – |
| Type | Open-weight | Proprietary | |
| Context window | 131K tokens | 262K tokens | SASakana Namazu |
| Input price | $0.15/M · free self-host | $0.95/M | |
| Output price | $0.6/M · free self-host | $4/M | |
| Vision / multimodal | No | Yes | SASakana Namazu |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | |
| License | Apache 2.0 | Proprietary |
Price gap & when to choose each
gpt-oss-120b (batch) is ~6.7× cheaper than Sakana Namazu on output tokens ($0.6 vs $4 per M tokens).
- You want to self-host or run on your cloud
- You prioritize data privacy & control
- You want the lowest operating costs
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You need the longer 262K context window
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | gpt-oss-120b (batch) | Sakana Namazu |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✗ | ✓ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✗ | ✗ |
Benchmarks: gpt-oss-120b (batch) vs Sakana Namazu
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How gpt-oss-120b (batch) and Sakana Namazu score
| Criterion | gpt-oss-120b (batch) | Sakana Namazu |
|---|---|---|
| Cost-efficiency | 5.0 | 4.0 |
| Context window | 3.5 | 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.
What each model is
gpt-oss-120b (batch) Open
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. It activates 5.1B parameters per forward pass and is optimize
Sakana Namazu Paid
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,...
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
Is gpt-oss-120b (batch) as good as Sakana Namazu?
gpt-oss-120b (batch) 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.
Can I run gpt-oss-120b (batch) locally?
Yes. gpt-oss-120b (batch) 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.
How much cheaper is gpt-oss-120b (batch)?
gpt-oss-120b (batch) costs $0.6/M output vs $4/M for Sakana Namazu — roughly 7x cheaper via API, and free if you self-host.
gpt-oss-120b (batch) vs Sakana Namazu — which should I pick in 2026?
Choose gpt-oss-120b (batch) 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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