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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. Nemotron 3.5 Lightning (Free)NVIDIARemove
  2. DeepSeek V4.1 FlashDeepSeekRemove
  3. Claude Opus 5.5AnthropicRemove
nemotron-3.5-lightning:free vs deepseek-v4.1-flash vs claude-opus-5.5
AttributeNemotron 3.5 Lightning (Free)nemotron-3.5-lightning:freeDeepSeek V4.1 Flashdeepseek-v4.1-flashClaude Opus 5.5claude-opus-5.5
Pricing
Input$0 / 1M$0.30 / 1M$4.00 / 1M
Output$0 / 1M$1.20 / 1M$20.00 / 1M
Cache Write$0 / 1M——
Cache Read$0 / 1M$0.30 / 1M$0.40 / 1M
Cache Write (5m)—$0.30 / 1M$5.00 / 1M
Cache Write (1h)—$0.30 / 1M$8.00 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max context1M1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderNVIDIADeepSeekAnthropic
Categorychatchatchat
Charge typeFreePay As You GoPay As You Go
Released———
Description
SummaryNVIDIA Nemotron 3.5 Lightning is an open Mixture-of-Experts (MoE) model with 30B total parameters and 3B active per token, optimized for high-throughput agentic workloads and efficient inference. Its lightweight active compute and open design make it well suited for specialized agents, domain-specific customization, and scalable production deployments where speed, cost efficiency, and adaptability are key.DeepSeek 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.Claude Opus 5.5 is Anthropic's flagship model for advanced reasoning, coding, and long-horizon agentic workflows, succeeding Opus 5. It excels at multi-step changes across large codebases, code review and bug detection, financial and scientific analysis, and understanding dense charts, diagrams, and screenshots, with stronger grounding when reporting figures and citing sources. Compared with Opus 5, it completes comparable tasks with fewer steps and lower token usage while providing clearer, more concise progress reporting. With adaptive thinking and configurable effort levels, Opus 5.5 can balance reasoning depth, latency, and cost, making it well suited for both demanding autonomous workflows and latency-sensitive professional tasks.