Model comparison
Compare NVIDIA Nemotron 3.5 Lightning and Qwen3.8-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) |
|---|---|---|
| NVIDIA Nemotron 3.5 LightningNVIDIA | NVIDIA | No reviewed rate |
| Qwen3.8-FlashQwen | Qwen | 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.
Alibaba's efficient million-context multimodal model for fast agents, coding, document work, vision, video understanding, and tool use.
Knowledge cutoff is not published, and regional Model Studio terms can differ from other Qwen gateways. Confirm the exact endpoint, long-context pricing, output limit, logging, and retention settings.
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 | Qwen3.8-Flash |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | Up to 1M tokens | Up to 1M tokens through Model Studio |
| Maximum outputProvider-published response limit, where available. | Not separately published | Up to 131,072 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 | $0.113 / 1M tokens |
| Output priceCurrent standard list price per million output tokens unless noted. | Free prototype or deployment cost | $0.382 / 1M tokens |
| InputsMedia types accepted by the listed model endpoint. | Text | Text, image, video |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Agentic tools and long-running workflows | Function calling, web search, structured output, tools |
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
Alibaba's public model page should be read together with the selected Model Studio region and account terms. Do not assume another Qwen gateway's retention or training setting applies to the Alibaba Cloud route.
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. Qwen3.8-Flash: Alibaba's efficient million-context multimodal model for fast agents, coding, document work, vision, video understanding, and tool use.
Consider NVIDIA Nemotron 3.5 Lightning when your priority is High-volume agent sub-tasks. Consider Qwen3.8-Flash when your priority is Cost-sensitive multimodal agents. 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.
