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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. Gemini 3.5 TranscribeGoogleRemove
  3. Gemini 4 ArgonGoogleRemove
  4. GLM 5.3Z.AIRemove

4 is the maximum. Remove one to add another.

deepseek-v4.1-flash vs gemini-3.5-transcribe vs gemini-4-argon vs glm-5.3
AttributeDeepSeek V4.1 Flashdeepseek-v4.1-flashGemini 3.5 Transcribegemini-3.5-transcribeGemini 4 Argongemini-4-argonGLM 5.3glm-5.3
Pricing
Input$0.30 / 1M— Not priced per input token$2.00 / 1M$1.40 / 1M
Output$1.20 / 1M— Not priced per output token$10.00 / 1M$4.40 / 1M
Cache Write (5m)$0.30 / 1MNot applicable$2.00 / 1M$1.40 / 1M
Cache Write (1h)$0.30 / 1MNot applicable$2.00 / 1M$1.40 / 1M
Cache Read$0.30 / 1MNot applicable$2.00 / 1M$1.40 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M98.3K1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesNo
Function CallingYesYesYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderDeepSeekGoogleGoogleZ.AI
Categorychatvoicechatchat
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.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.