Mistral Large 4 Open vs SASakana Namazu Paid
Mistral Large 4 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.
$4.18 /M outputNo per-token fees if you self-host
$4 /M outputManaged API (no infra to run)
Mistral Large 4 vs Sakana Namazu specs
| Spec | Mistral Large 4 | Sakana Namazu | Winner |
|---|---|---|---|
| Maker | Mistral AI | Sakana AI | – |
| Type | Open-weight | Proprietary | |
| Context window | 1M tokens | 262K tokens | |
| Input price | $1.36/M · free self-host | $0.95/M | SASakana Namazu |
| Output price | $4.18/M · free self-host | $4/M | SASakana Namazu |
| Vision / multimodal | Yes | Yes | = Tie |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | |
| License | Apache 2.0 | Proprietary |
Price gap & when to choose each
- You want to self-host or run on your cloud
- You need the longer 1M context window
- You prioritize data privacy & control
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Mistral Large 4 | Sakana Namazu |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✓ | ✓ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✓ | ✗ |
Benchmarks: Mistral Large 4 vs Sakana Namazu
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Mistral Large 4 and Sakana Namazu score
| Criterion | Mistral Large 4 | Sakana Namazu |
|---|---|---|
| Cost-efficiency | 4.0 | 4.0 |
| Context window | 5.0 | 4.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 5.0 | 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
Mistral Large 4 Open
Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads. It offers a 1M-token context window with up...
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 Mistral Large 4 as good as Sakana Namazu?
Mistral Large 4 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 Mistral Large 4 locally?
Yes. Mistral Large 4 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.
Mistral Large 4 vs Sakana Namazu — which should I pick in 2026?
Choose Mistral Large 4 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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