DeepSeek: DeepSeek V4.1 Flash (batch)
DeepSeek: DeepSeek V4.1 Flash (batch) ranks #28 of 96 models by Artificial Analysis quality score (28.6) at $0.26/1M tokens blended - and ranks #2 of 404 by average real OpenRouter usage share over the trailing 125-day window (21.42%). Available from 40 providers at up to 100.0% uptime.
- Quality (Intelligence Index) - 28.6
- Coding index - -
- Agentic index - -
- Price (blended $/1M) - 0.26
- Context window - 1,048,576
- Usage rank - #2 of 404
- Providers - 40
- Open/closed - open
Usage share over time
What DeepSeek: DeepSeek V4.1 Flash (batch) is actually used for
Share of each real task category's classified traffic this model handles, from OpenRouter's task classification.
| Task | Share of task traffic |
|---|---|
| Security Audit | 55.7% |
| DevOps & Config | 52.4% |
| Shell Execution | 39.5% |
| Code Generation | 39.2% |
| Repo Scanning | 37.6% |
| File I/O | 36.7% |
| Web Search | 35.1% |
| Frontend & UI | 33.2% |
Compare DeepSeek: DeepSeek V4.1 Flash (batch)
Frequently asked questions
What is DeepSeek: DeepSeek V4.1 Flash (batch)'s quality score?
DeepSeek: DeepSeek V4.1 Flash (batch) scores 28.6 on Artificial Analysis's Intelligence Index, ranking #28 of 96 models with a published score.
How much does DeepSeek: DeepSeek V4.1 Flash (batch) cost?
DeepSeek: DeepSeek V4.1 Flash (batch) costs $0.26 per 1M tokens (blended 75% prompt / 25% completion pricing).
Is DeepSeek: DeepSeek V4.1 Flash (batch) widely used?
DeepSeek: DeepSeek V4.1 Flash (batch) ranks #2 of 404 models by average real OpenRouter usage share, averaging 21.42% of classified token volume over the trailing 125-day window.
Is DeepSeek: DeepSeek V4.1 Flash (batch) open-weight or closed?
DeepSeek: DeepSeek V4.1 Flash (batch) is an open-weight model.
Source: OpenRouter (openrouter.ai/rankings), as of November 7, 2026.
Benchmark scores: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings).
Methodology: www.smophy.ai/benchmark/methodology
Token counts originate from each provider's own tokenizer and are not directly comparable across providers.
