DeepSeek-V4.1-Flash model official release. This is the smallest model in DeepSeek’s new model-architecture series, featuring native multimodal visual understanding capabilities. The new architecture is designed to deliver a higher capability ceiling, faster inference speeds, greater throughput, and scalability to larger-parameter models.
Pricing
Eingabemodalitäten
- Text
- Vision
Ausgabemodalitäten
- Text
Context length
- 1M tokens
Max output
- 384K tokens
Capabilities
- Thinking
- Streaming
- Tool calling
- Web search
- URL context
- Code interpreter
- Computer use
- File search
- Memory tool
- Structured outputs
- Structured decision
- Citations
- Prompt caching
- Background mode
- Server-side sessions
Anbieter
Bytedance doubao-deepseek-v4.1-flash
Nebenzeiten04:00–06:00, 10:00–01:00 UTC
Pricing$0.1408$0.5632
Cache Storage$0.0024/h/M tokens
Cache Read$0.0028/M tokens
Web Search$0.0031/request
Spitzenzeiten01:00–04:00, 06:00–10:00 UTC
Pricing$0.2816$1.1264
Cache Storage$0.0024/h/M tokens
Cache Read$0.0056/M tokens
Web Search$0.0031/request
PrecisionⓘNot Disclosed
Latency5.9S
Throughput66.5TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Baidu baidu-deepseek-v4.1-flash
Nebenzeiten14:00–00:00 UTC
Pricing$0.1408$0.5632
Cache Read$0.0028/M tokens
Spitzenzeiten00:00–14:00 UTC
Pricing$0.2816$1.1264
Cache Read$0.0056/M tokens
PrecisionⓘNot Disclosed
Latency3.2S
Throughput78.3TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Tencent tencent-deepseek-v4.1-flash
Nebenzeiten04:00–06:00, 10:00–01:00 UTC
Pricing$0.155$0.62
Cache Read$0.0031/M tokens
Spitzenzeiten01:00–04:00, 06:00–10:00 UTC
Pricing$0.3098$1.2392
Cache Read$0.0062/M tokens
PrecisionⓘNot Disclosed
Latency1.9S
Throughput8.1TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Pareto pareto-deepseek-v4.1-flash
Nebenzeiten04:00–06:00, 10:00–01:00 UTC
Pricing$0.155$0.62
Cache Read$0.0031/M tokens
Web Search$0.00077/request
Spitzenzeiten01:00–04:00, 06:00–10:00 UTC
Pricing$0.3098$1.2392
Cache Read$0.0062/M tokens
Web Search$0.00077/request
PrecisionⓘNot Disclosed
Latency1.6S
Throughput11.4TPS
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
100.00% uptime today
Alibaba Cloud alicloud-deepseek-v4.1-flash
Nebenzeiten14:00–00:00 UTC
Pricing$0.1408$0.5632
Cache Read$0.0141/M tokens
Web Search$0.00062/request
Spitzenzeiten00:00–14:00 UTC
Pricing$0.2816$1.1264
Cache Read$0.0282/M tokens
Web Search$0.00062/request
PrecisionⓘNot Disclosed
Latency0.9S
Throughput17.0TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Morph morph-deepseek-v4.1-flash
Nebenzeiten04:00–06:00, 10:00–01:00 UTC
Pricing$0.155$0.62
Cache Read$0.0031/M tokens
Spitzenzeiten01:00–04:00, 06:00–10:00 UTC
Pricing$0.3098$1.2392
Cache Read$0.0062/M tokens
PrecisionⓘNot Disclosed
Latency0.8S
Throughput16.5TPS
Uptime
100.00% uptime 2 days ago
100.00% uptime yesterday
100.00% uptime today
Azure azure-deepseek-v4.1-flash
Pricing$0.3$1.2
Cache$0.006
PrecisionⓘNot Disclosed
Latency-
Throughput-
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Deepinfra deepinfra-deepseek-v4.1-flash
Nebenzeiten04:00–06:00, 10:00–01:00 UTC
Pricing$0.155$0.62
Cache Read$0.0031/M tokens
Spitzenzeiten01:00–04:00, 06:00–10:00 UTC
Pricing$0.3098$1.2392
Cache Read$0.0062/M tokens
PrecisionⓘFP8
Latency-
Throughput-
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Atlas atlas-deepseek-v4.1-flash
Pricing$0.3$1.2
Cache$0.03
PrecisionⓘNot Disclosed
Latency-
Throughput-
Uptime
0.00% uptime 2 days ago
0.00% uptime yesterday
0.00% uptime today
Performance for deepseek-v4.1-flash
Uptime ist der Prozentsatz der erfolgreichen Anfragen in den letzten 72 Stunden. AIHubMix überwacht jeden Anbieter kontinuierlich und wiederholt Anfragen automatisch beim nächstbesten Anbieter, wenn einer einen Fehler zurückgibt oder zu langsam antwortet; Latency ist die gesamte Umlaufzeit einer Anfrage (niedriger ist besser); Throughput gibt an, wie schnell das Modell schreibt (Tokens pro Sekunde, höher ist besser).
Uptime
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Latency
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Try this model
Python