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Compare models

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 FlashDeepSeekRemove
  2. Qwen3.8 27BAlibabaRemove
  3. Perceptron Mk1.5PerceptronRemove
  4. Nemotron 3.5 Super VLNVIDIARemove

4 is the maximum. Remove one to add another.

deepseek-v4.1-flash vs qwen3.8-27b vs perceptron-mk1.5 vs nemotron-3.5-super-vl
AttributeDeepSeek V4.1 Flashdeepseek-v4.1-flashQwen3.8 27Bqwen3.8-27bPerceptron Mk1.5perceptron-mk1.5Nemotron 3.5 Super VLnemotron-3.5-super-vl
Pricing
Input$0.30 / 1M$0.45 / 1M$0.15 / 1M$0.10 / 1M
Output$1.20 / 1M$3.20 / 1M$1.50 / 1M$0.40 / 1M
Cache Write (5m)$0.30 / 1M$0.45 / 1M$0.15 / 1M$0.10 / 1M
Cache Write (1h)$0.30 / 1M$0.45 / 1M$0.15 / 1M$0.10 / 1M
Cache Read$0.30 / 1M$0.45 / 1M$0.15 / 1M$0.10 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M262K36.9K1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesYesYes
Catalogue
ProviderDeepSeekAlibabaPerceptronNVIDIA
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-09-25—
Description
SummaryDeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications.