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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. Olmo 3 32B ThinkAllen AIRemove
deepseek-v4.1-flash-1017 vs olmo-3-32b-think
AttributeDeepSeek V4.1 Flash 1017deepseek-v4.1-flash-1017Olmo 3 32B Thinkolmo-3-32b-think
Pricing
Input$0.10 / 1M$0.30 / 1M
Output$0.50 / 1M$0.45 / 1M
Cache Write (5m)$0.10 / 1M$0.30 / 1M
Cache Write (1h)$0.10 / 1M$0.30 / 1M
Cache Read$0.10 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M65.5K
Max outputN/AN/A
Capabilities
VisionYesNo
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderDeepSeekAllen AI
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.Olmo 3.1 32B Think is a 32B-parameter reasoning model built for complex, multi-step logic and advanced instruction following. It improves on earlier Olmo versions with more refined reasoning and stronger performance on challenging evaluations, and — as part of AI2’s open initiative — it's fully transparent and released under Apache 2.0 with open weights, code, and training details.