DeepSeek V4.1 Flash 1017 (batch) is $0.07 cheaper per 1M input tokens (86.2% lower; 7.27x difference).
API cost decision in 10 seconds
NewDeepSeek V4.1 Flash 1017 (batch) vs Ternary Bonsai 2 9B
Pick DeepSeek V4.1 Flash 1017 (batch) 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 DeepSeek V4.1 Flash 1017 (batch) when budget and context both matter.
On the standard 1M input plus 500K output workload, DeepSeek V4.1 Flash 1017 (batch) is estimated at $0.11 vs $0.15 for Ternary Bonsai 2 9B, saving $0.03 (23.4% lower).
Cost-first pickDeepSeek V4.1 Flash 1017 (batch)
Context-first pickDeepSeek V4.1 Flash 1017 (batch)
Sample savings$0.0323.4%
10x traffic gap$0.34
DeepSeek V4.1 Flash 1017 (batch) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $0.34. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Cost winner changes by workload shape: input-heavy / RAG favors DeepSeek V4.1 Flash 1017 (batch), balanced workload favors Ternary Bonsai 2 9B, and output-heavy chatbot favors Ternary Bonsai 2 9B.
| Workload shape | Token mix | Better pick | DeepSeek V4.1 Flash 1017 (batch) | Ternary Bonsai 2 9B |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | DeepSeek V4.1 Flash 1017 (batch) | $0.15 | $0.47 |
| Balanced workload | 1M input + 1M output | Ternary Bonsai 2 9B | $0.21 | $0.21 |
| Output-heavy chatbot | 1M input + 5M output | Ternary Bonsai 2 9B | $1.01 | $0.73 |
Ternary Bonsai 2 9B is $0.07 cheaper per 1M output tokens (35% lower; 1.54x difference).
DeepSeek V4.1 Flash 1017 (batch) has 786.43K more context (4x larger).
DeepSeek V4.1 Flash 1017 (batch) is $0.03 cheaper on the standard workload (23.4% 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
DeepSeek V4.1 Flash 1017 (batch) has the lower input price; Ternary Bonsai 2 9B has the lower output price; DeepSeek V4.1 Flash 1017 (batch) offers the larger context window. For the 1M input plus 500K output sample, DeepSeek V4.1 Flash 1017 (batch) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.11 for DeepSeek V4.1 Flash 1017 (batch) and $0.15 for Ternary Bonsai 2 9B.
Choose DeepSeek V4.1 Flash 1017 (batch) when you care most about lower input-token price, and larger context window.
Choose Ternary Bonsai 2 9B when you care most about lower output-token price.
- On the standard 1M input plus 500K output workload, DeepSeek V4.1 Flash 1017 (batch) is estimated at $0.11 vs $0.15 for Ternary Bonsai 2 9B, saving $0.03 (23.4% lower).
- DeepSeek V4.1 Flash 1017 (batch) is $0.03 cheaper on the standard workload (23.4% lower).
- DeepSeek V4.1 Flash 1017 (batch) is $0.07 cheaper per 1M input tokens (86.2% lower; 7.27x difference).
- Ternary Bonsai 2 9B is $0.07 cheaper per 1M output tokens (35% lower; 1.54x difference).
- DeepSeek V4.1 Flash 1017 (batch) has 786.43K more context (4x larger).
| Feature | NewDeepSeek V4.1 Flash 1017 (batch) (DeepSeek) | Ternary Bonsai 2 9B (PrismML) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.011 | $0.08 |
| Completion Price per 1M tokens | $0.2 | $0.13 |
| Sample Workload Cost 1M input + 500K output | $0.11 | $0.15 |
| Context Window | 1.05M | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | DeepSeek V4.1 Flash 1017 (batch) | On the standard 1M input plus 500K output workload, DeepSeek V4.1 Flash 1017 (batch) is estimated at $0.11 vs $0.15 for Ternary Bonsai 2 9B, saving $0.03 (23.4% lower). |
| High-volume input processing | DeepSeek V4.1 Flash 1017 (batch) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Ternary Bonsai 2 9B | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | DeepSeek V4.1 Flash 1017 (batch) | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- DeepSeek V4 Flash 0731 (free) can replace DeepSeek V4.1 Flash 1017 (batch) when lower sample workload cost matters most: $0.
- DeepSeek V4 Flash (free) can replace DeepSeek V4.1 Flash 1017 (batch) when lower sample workload cost matters most: $0.
- GPT-6 Luna Pro (batch) offers 1.05M context with $0.17 sample workload cost.
- GPT-6 Luna (batch) offers 1.05M context with $0.17 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- Kimi K3.1 Pro · MoonshotAI · #1
- DeepSeek V4.1 Flash 1017 · DeepSeek · #2
- DeepSeek V4.1 Flash · DeepSeek · #3
- GLM 5.3 Flash · Z.ai · #4
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Open PrismML modelsDeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek V4.1 Flash, served by DeepSeek under the `deepseek-flash` API model name. V4.1 Flash is a sparse mixture-of-experts model...
Ternary Bonsai 2 9B is PrismML’s compact, open-weight language model for conversational AI, reasoning, and tool use. Built on Qwen3.5, it uses ternary weights packed into 2 bits for efficient...