Nemotron 3.5 Lightning benchmarks, pricing and specs
Nemotron 3.5 Lightning is a NVIDIA model released on August 11, 2026 that takes text input and produces text. Its price is not published and accepts up to 1,000,000 tokens of context. It scores 1349 Elo on Arena Text, #47 of 49 current models (Arena, measured October 8, 2026).
- Context window
- 1M
- Arena Text
- 1349 Elo · #47/49
Data verified October 13, 2026 · Dataset 2026-10-13
Key facts
- Provider
- NVIDIA
- Model family
- Nemotron 3.5
- Release date
- August 11, 2026
- Status
- Current
- Access
- open weights
- API model id
- Not reported
- Context window
- 1,000,000 tokens
- Max output
- Not reported
- Input
- text
- Output
- text
- Task families
- text
- Declared capabilities
- reasoning, agentic coding
Nemotron 3.5 Lightning pricing
Independent benchmark results
Scores come from independent evaluators that ran the model themselves, pinned to a dated snapshot. Rank is among current models in the same snapshot. NVIDIA's own launch figures are listed under strengths with the publisher named, because they are not measured the same way.
| Benchmark | Score | Rank | Measured | Source |
|---|---|---|---|---|
| Arena Text | 1349 Elo | #47 of 49 | October 8, 2026 | Arena · 2026-10-12 |
Strengths, cautions and best uses
Strengths
- A 30B mixture-of-experts model with 3B active parameters; NVIDIA reports up to 4x the output speed of similar-sized models
- Weights, training data and recipes are released under the OpenMDW-1.1 licence, in BF16 and NVFP4
- Context of up to 1M tokens, or 256K on a single H100
Cautions
- On NVIDIA's own table it trails Qwen 3.6 35B A3B on SWE-bench Verified (51.56 against 70.12)
- NVIDIA sells no per-token API for it; hosted prices come from third parties
Best for
- Fast, low-cost agent subtasks such as tool calls
- Self-hosted agents on one GPU
Alternatives to Nemotron 3.5 Lightning
The closest current textmodels by price. The cheapest model that scores as well or better is listed first; failing that, the cheapest one within 3% of the benchmark's scale.
Grok 4.6
- 105 points higher on Arena Text, 1454 vs 1349
- 500K context window vs 1M
- From xAI
Muse Glimmer
- 76 points higher on Arena Text, 1425 vs 1349
- 131K context window vs 1M
- From Meta
DeepSeek-V4-Pro
- 116 points higher on Arena Text, 1465 vs 1349
- From DeepSeek
Gemini 3.7 Flash
- 137 points higher on Arena Text, 1486 vs 1349
- From Google
Compare Nemotron 3.5 Lightning with
Nemotron 3.5 Lightning FAQ
What is the context window of Nemotron 3.5 Lightning?
Nemotron 3.5 Lightning accepts up to 1,000,000 tokens of context. That ranks #25 of 57 current text models by context length.
How does Nemotron 3.5 Lightning score on independent benchmarks?
Nemotron 3.5 Lightning scores 1349 Elo on Arena Text, #47 of 49 current models (Arena, measured October 8, 2026). These are independent evaluations, not NVIDIA's own launch figures.
Is Nemotron 3.5 Lightning open source or API only?
Nemotron 3.5 Lightning is released as open weights that you can run yourself.
What are the best alternatives to Nemotron 3.5 Lightning?
The closest current alternatives by price and measured performance are Grok 4.6 (105 points higher on Arena Text, 1454 vs 1349), Muse Glimmer (76 points higher on Arena Text, 1425 vs 1349), DeepSeek-V4-Pro (116 points higher on Arena Text, 1465 vs 1349) and Gemini 3.7 Flash (137 points higher on Arena Text, 1486 vs 1349).
Sources
- NVIDIA Nemotron 3.5 Lightning 30B-A3B model card · NVIDIA · official · verified October 13, 2026
- NVIDIA Nemotron 3.5 Lightning announcement · NVIDIA · official · verified October 13, 2026
- Arena leaderboard dataset (lmarena-ai/leaderboard-dataset) · Arena · independent · verified October 12, 2026 · CC-BY-4.0
Cite this page
Van Data Team. "Nemotron 3.5 Lightning Benchmarks, Pricing and Specs." AI Model Benchmark Dataset 2026-10-13. https://vandatateam.com/ai-model-benchmarks/nemotron-3-5-lightning
Reuse the data: JSON · CSV · or explore every model in the AI model benchmark comparison.
Production evaluation
Deciding whether Nemotron 3.5 Lightning fits your workload?
Public benchmarks narrow the shortlist. We test the finalists on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- Evaluation cases and acceptance thresholds tied to real work
- Model routing, fallbacks and cost controls
