Hy4 is $0.53 cheaper per 1M input tokens (56.1% lower; 2.28x difference).
API cost decision in 10 seconds
NewHy4 vs Sakana Namazu
Pick Hy4 when budget and context both matter.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Hy4 when budget and context both matter.
On the standard 1M input plus 500K output workload, Hy4 is estimated at $1.04 vs $2.95 for Sakana Namazu, saving $1.91 (64.7% lower).
Cost-first pickHy4
Context-first pickHy4
Sample savings$1.9164.7%
10x traffic gap$19.08
Hy4 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $19.08. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Hy4 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Hy4 | Sakana Namazu |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Hy4 | $2.71 | $6.75 |
| Balanced workload | 1M input + 1M output | Hy4 | $1.67 | $4.95 |
| Output-heavy chatbot | 1M input + 5M output | Hy4 | $6.67 | $20.95 |
Hy4 is $2.75 cheaper per 1M output tokens (68.7% lower; 3.2x difference).
Hy4 has 786.43K more context (4x larger).
Hy4 is $1.91 cheaper on the standard workload (64.7% lower).
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
Hy4 has the lower input price; Hy4 has the lower output price; Hy4 offers the larger context window. For the 1M input plus 500K output sample, Hy4 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.04 for Hy4 and $2.95 for Sakana Namazu.
Choose Hy4 when you care most about lower input-token price, lower output-token price, and larger context window.
Choose Sakana Namazu when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
- On the standard 1M input plus 500K output workload, Hy4 is estimated at $1.04 vs $2.95 for Sakana Namazu, saving $1.91 (64.7% lower).
- Hy4 is $1.91 cheaper on the standard workload (64.7% lower).
- Hy4 is $0.53 cheaper per 1M input tokens (56.1% lower; 2.28x difference).
- Hy4 is $2.75 cheaper per 1M output tokens (68.7% lower; 3.2x difference).
- Hy4 has 786.43K more context (4x larger).
| Feature | NewHy4 (Tencent) | Sakana Namazu (Sakana) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.417 | $0.95 |
| Completion Price per 1M tokens | $1.2505 | $4 |
| Sample Workload Cost 1M input + 500K output | $1.04 | $2.95 |
| Context Window | 1.05M | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Hy4 | On the standard 1M input plus 500K output workload, Hy4 is estimated at $1.04 vs $2.95 for Sakana Namazu, saving $1.91 (64.7% lower). |
| High-volume input processing | Hy4 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Hy4 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Hy4 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Hy3 (free) can replace Hy4 when lower sample workload cost matters most: $0.
- Hy-MT2-1.8B can replace Hy4 when lower sample workload cost matters most: $0.13.
- Hy-MT2-30B-A3B can replace Hy4 when lower sample workload cost matters most: $0.22.
- Hy-MT2-7B can replace Hy4 when lower sample workload cost matters most: $0.22.
- Grok 4.20 Multi-Agent offers 2M context with $2.5 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- Llama 4 Scout offers 1.31M context with $0.25 sample workload cost.
- GPT-6 Luna offers 1.05M context with $0.35 sample workload cost.
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Cheaper alternatives
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Open Sakana modelsThe official release of Hy4 delivers comprehensive and substantial improvements over Hy4 Preview, with particularly strong gains in agentic capabilities and performance across a wide range of long-horizon, real-world productivity...
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,...