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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. DeepSeek V4.1 Flash 1017DeepSeekRemove
  2. Qwen3.5-122B-A10BAlibabaRemove
deepseek-v4.1-flash-1017 vs qwen3.5-122b-a10b
AttributeDeepSeek V4.1 Flash 1017deepseek-v4.1-flash-1017Qwen3.5-122B-A10Bqwen3.5-122b-a10b
Pricing
Input$0.10 / 1M$0.40 / 1M
Output$0.50 / 1M$3.20 / 1M
Cache Write (5m)$0.10 / 1M$0.40 / 1M
Cache Write (1h)$0.10 / 1M$0.40 / 1M
Cache Read$0.10 / 1M$0.40 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M262.1K
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderDeepSeekAlibaba
Categorychatchat
Charge typePay As You GoPay As You Go
Released——
Description
SummaryDeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek’s cost-efficient Mixture-of-Experts (MoE) model, built on its innovative Causal Encoder-Decoder (CED) architecture. Featuring 552B total parameters with 8B activated for input and 16B for output, it combines efficient inference with native multimodal understanding through jointly trained text and visual representations. Optimized for coding, terminal and computer-use agents, and long-horizon workflows, the model introduces compressed KV caching that reduces cache memory usage to approximately one-quarter of the previous Flash generation. DeepSeek reports that it surpasses V4 Pro in performance, inference speed, and task completion time, making it well suited for cost-efficient autonomous agents, complex software engineering, and long-context analysis.Qwen3.5-122B-A10B is a native vision-language model built on a hybrid architecture that combines linear attention mechanisms with a sparse Mixture-of-Experts (MoE) design for improved inference efficiency. In overall performance, it ranks just below Qwen3.5-397B-A17B, delivering substantial gains over previous generations. Its text capabilities significantly exceed Qwen3-235B-2507, while its visual performance surpasses Qwen3-VL-235B, making it a strong high-end option for advanced multimodal and agent-driven applications.