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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. Qwen3 Next 80B A3B InstructAlibabaRemove
  2. DeepSeek V4.1 Flash 1017DeepSeekRemove
qwen3-next-80b-a3b-instruct vs deepseek-v4.1-flash-1017
AttributeQwen3 Next 80B A3B Instructqwen3-next-80b-a3b-instructDeepSeek V4.1 Flash 1017deepseek-v4.1-flash-1017
Pricing
Input$0.10 / 1M$0.10 / 1M
Output$0.40 / 1M$0.50 / 1M
Cache Write (5m)$0.10 / 1M$0.10 / 1M
Cache Write (1h)$0.10 / 1M$0.10 / 1M
Cache Read$0.10 / 1M$0.10 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context262.1K1M
Max outputN/AN/A
Capabilities
VisionNoYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderAlibabaDeepSeek
Categorychatchat
Charge typePay As You GoPay As You Go
Released——
Description
SummaryQwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model optimized for fast, stable answers without exposing chain-of-thought. It handles complex reasoning, code generation, knowledge QA, and multilingual tasks with strong alignment and formatting reliability. Designed for high throughput and stability on ultra-long inputs and multi-turn conversations, it’s well suited for RAG, tool use, and agent workflows where consistent final outputs matter. It delivers near–large-model performance with efficient inference, making it a strong choice for production assistants and long-context problem solving.DeepSeek 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.