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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. Gemini 4 HydrogenGoogleRemove
  2. DeepSeek V4.1 Flash 1017DeepSeekRemove
  3. S1Fish AudioRemove
  4. Gemini 4 ArgonGoogleRemove

4 is the maximum. Remove one to add another.

gemini-4-hydrogen vs deepseek-v4.1-flash-1017 vs s1 vs gemini-4-argon
AttributeGemini 4 Hydrogengemini-4-hydrogenDeepSeek V4.1 Flash 1017deepseek-v4.1-flash-1017S1s1Gemini 4 Argongemini-4-argon
Pricing
Input$1.50 / 1M$0.20 / 1M— Not priced per input token$2.00 / 1M
Output$7.50 / 1M$0.80 / 1M— Not priced per output token$10.00 / 1M
Cache Write (5m)$1.50 / 1M$0.20 / 1MNot applicable$2.00 / 1M
Cache Write (1h)$1.50 / 1M$0.20 / 1MNot applicable$2.00 / 1M
Cache Read$1.50 / 1M$0.20 / 1MNot applicable$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1MN/A1M
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesNoYes
Function CallingYesYesNoYes
JSON ModeYesYesNoYes
StreamingYesYesNoYes
Catalogue
ProviderGoogleDeepSeekFish AudioGoogle
Categorychatchatvoicechat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released——2026-07-29—
Description
SummaryGemini 4 Hydrogen is Google's high-efficiency multimodal model in the Gemini 4 family, optimized for high-throughput agentic workflows, coding, and multi-model routing. It delivers strong performance at lower cost and latency than Gemini 4 Carbon, supporting text, image, audio, video, and file inputs for versatile multimodal applications. Designed for scalable production workloads and long-horizon execution, Gemini 4 Hydrogen supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high, and xhigh) to balance reasoning depth, speed, and cost. It is well suited for coding assistants, autonomous agents, complex workflow automation, and large-scale AI systems.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.Fish Audio S1 text-to-speech. Billed per UTF-8 byte of input text.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.