Model comparison
Compare NVIDIA Nemotron 3.5 Lightning and DeepSeek-V4-Flash using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
Set your usage. Your estimate updates as you type.
Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.
One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| DeepSeek-V4-FlashDeepSeek | DeepSeek | No reviewed rate |
| NVIDIA Nemotron 3.5 LightningNVIDIA | NVIDIA | No reviewed rate |
Quick take
NVIDIA's compact 30B mixture-of-experts model for efficient specialist agents and high-volume text workflows.
The current release is labeled preview. Validate the exact precision, language, tool template, provider route, and long-context memory needs before standardizing a production fleet.
DeepSeek's lower-cost V4 model for high-volume reasoning, coding, agents, and million-token text workloads.
Flash's knowledge cutoff and universal latency are not published. Do not confuse it with Flash-Vision-Exp, and verify peak pricing, cache behavior, output budgets, jurisdiction, and data handling.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Text & reasoning | NVIDIA Nemotron 3.5 Lightning | DeepSeek-V4-Flash |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | Up to 1M tokens | 1M tokens |
| Maximum outputProvider-published response limit, where available. | Not separately published | Up to 384K tokens |
| Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff. | Pretraining through Sep 2025; post-training through May 2026 | Not published |
| Input priceCurrent standard list price per million input tokens unless noted. | Free prototype or deployment cost | $0.44 / 1M peak uncached; $0.22 off-peak |
| Output priceCurrent standard list price per million output tokens unless noted. | Free prototype or deployment cost | $1.32 / 1M peak; $0.66 off-peak |
| InputsMedia types accepted by the listed model endpoint. | Text | Text; separate Flash-Vision-Exp accepts images |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Agentic tools and long-running workflows | Tools, JSON output, Responses API, thinking effort, FIM beta |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
Self-hosted weights keep request data under the operator's controls. NVIDIA API trials, OpenRouter, and cloud partners each apply separate logging, retention, and training-use policies.
Provider and API links
DeepSeek documents its Responses API as stateless and says responses and conversations are not stored by that endpoint. This is not a complete account-wide retention or training-use promise; review current platform terms and automatic cache behavior for sensitive data.
Provider and API links
Frequently asked questions
NVIDIA Nemotron 3.5 Lightning: NVIDIA's compact 30B mixture-of-experts model for efficient specialist agents and high-volume text workflows. DeepSeek-V4-Flash: DeepSeek's lower-cost V4 model for high-volume reasoning, coding, agents, and million-token text workloads.
Consider NVIDIA Nemotron 3.5 Lightning when your priority is High-volume agent sub-tasks. Consider DeepSeek-V4-Flash when your priority is Cost-efficient coding and agent workloads. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
