AI model comparison
Nemotron 3.5 Super VL vs GPT-6 Luna
Side by side comparison of Nemotron 3.5 Super VL and GPT-6 Luna on pricing, benchmark scores, context window, and more.
NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total.
- Input / 1M
- $0.15
- Output / 1M
- $0.50
- Context
- 1.05M
GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol.
- Input / 1M
- $0.10
- Output / 1M
- $0.50
- Context
- 1.05M
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
GPT-6 Luna
1.2x cheaper for a typical chat
Higher intelligence score
GPT-6 Luna
27.8 vs 13.6 on Artificial Analysis
Larger context window
GPT-6 Luna
1.05M vs 1.05M tokens
Newer release
Nemotron 3.5 Super VL
Released October 15, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
GPT-6 Luna27.8Coding index
GPT-6 LunaNot availableAgentic index
GPT-6 LunaNot availablePricing
Nemotron 3.5 Super VL vs GPT-6 Luna API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | GPT-6 Luna | |
|---|---|---|
| Input tokensPer 1M tokens | $0.15 | $0.10 |
| Output tokensPer 1M tokens | $0.50 | $0.50 |
| Cached input (read)Per 1M tokens | $0.02 | $0.01 |
| Cache writePer 1M tokens | Not available | $0.13 |
| Long-context pricingPer 1M tokens, for very long prompts | Same rate at any length | $0.20 in / $0.75 out above 272K |
| Web searchPer request | Not available | $0.01 |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
GPT-6 Luna$0.45Coding task
30K in, 4K out
GPT-6 Luna$5$2.30 cachedLong document summary
150K in, 2K out
GPT-6 Luna$16$2.50 cachedSpecs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | GPT-6 Luna | |
|---|---|---|
| Context window | 1.05M tokens | 1.05M tokens |
| Max output | 236K tokens | 128K tokens |
| Input types | Image, Text, Video | File, Image, Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Max, Extra high, High, Medium, Low, None |
| Default reasoning effort | Not available | Medium |
| Release date | October 15, 2026 | September 22, 2026 |
Features
Supported features
API features available for each model.
| Metric | GPT-6 Luna | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Not supported |
| Stop sequences | Supported | Not supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
- Nemotron 3.5 Super VL vs Qwen3.8 27B
- Nemotron 3.5 Super VL vs MiniMax M3
- Nemotron 3.5 Super VL vs Inkling Small
- Nemotron 3.5 Super VL vs Inkling
- Nemotron 3.5 Super VL vs Nemotron 3 Ultra
- Nemotron 3.5 Super VL vs Gemini 3.5 Flash Lite
- Nemotron 3.5 Super VL vs Muse Glimmer 30B
- Nemotron 3.5 Super VL vs DeepSeek V4.1 Flash 1017
- Nemotron 3.5 Super VL vs DeepSeek V4.1 Flash
- Nemotron 3.5 Super VL vs GLM 5.3 Flash
- Nemotron 3.5 Super VL vs Hy3
GPT-6 LunaView full model details- GPT-6 Luna vs DeepSeek V4.1 Flash 1017
- GPT-6 Luna vs DeepSeek V4.1 Flash
- GPT-6 Luna vs GLM 5.3 Flash
- GPT-6 Luna vs Hy4 preview
- GPT-6 Luna vs Claude Opus 5.5
- GPT-6 Luna vs GLM 5.3
- GPT-6 Luna vs Step 5 Preview
- GPT-6 Luna vs MiMo-V2.6-Flash
- GPT-6 Luna vs DeepSeek V4 Flash 0731
- GPT-6 Luna vs Hy3
- GPT-6 Luna vs GPT-6.1 Sol
- GPT-6 Luna vs Claude Haiku 5.5
- GPT-6 Luna vs DeepSeek V4 Flash 0423
- GPT-6 Luna vs GPT-6 Astra
- GPT-6 Luna vs MiniMax M3.1 Flash
- GPT-6 Luna vs Muse Spark 1.3 Contributor
- GPT-6 Luna vs Claude Sonnet 5.5
- GPT-6 Luna vs GPT-6.1 Terra
- GPT-6 Luna vs Gemini 4 Argon
- GPT-6 Luna vs GPT-5.6 Luna
- GPT-6 Luna vs Gemini 3.8 Flash
- GPT-6 Luna vs MiMo-V2.6-Pro
- GPT-6 Luna vs Solar Mini 4
- GPT-6 Luna vs MiniMax M3
- GPT-6 Luna vs Qwen3.8 Max (0902)
- GPT-6 Luna vs DeepSeek V4 Pro 0813
- GPT-6 Luna vs Solar Pro 4
- GPT-6 Luna vs Qwen3.8 Flash
- GPT-6 Luna vs Mistral Large 4
- GPT-6 Luna vs Qwen3.8 27B
- GPT-6 Luna vs GPT-6 Luna Pro
- GPT-6 Luna vs Gemma 4 31B
- GPT-6 Luna vs gpt-oss-120b
- GPT-6 Luna vs Qwen3.7 Flash
- GPT-6 Luna vs Gemma 4 26B A4B
- GPT-6 Luna vs Gemini 2.5 Flash Lite
- GPT-6 Luna vs Step 3.7 Flash
- GPT-6 Luna vs DeepSeek V3.2
- GPT-6 Luna vs GPT-4o-mini
- GPT-6 Luna vs gpt-oss-20b
- GPT-6 Luna vs GLM 5.3 FlashX
- GPT-6 Luna vs Qwen3.6 35B A3B
- GPT-6 Luna vs GPT-5.6 Luna Pro
- GPT-6 Luna vs Ling 3.1 Flash
Our take
GPT-6 Luna is 1.2x cheaper for a typical chat. GPT-6 Luna scores higher on the Artificial Analysis Intelligence Index (27.8 vs 13.6). GPT-6 Luna has the larger context window (1.05M vs 1.05M tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Nemotron 3.5 Super VL or GPT-6 Luna cheaper?
GPT-6 Luna is cheaper for a typical chat (2K input tokens and 500 output tokens). GPT-6 Luna costs $0.10 per 1M input tokens and $0.50 per 1M output tokens, while Nemotron 3.5 Super VL costs $0.15 per 1M input tokens and $0.50 per 1M output tokens.
Which has a bigger context window, Nemotron 3.5 Super VL or GPT-6 Luna?
GPT-6 Luna supports up to 1.05M tokens of context, compared with 1.05M for Nemotron 3.5 Super VL.
Is Nemotron 3.5 Super VL smarter than GPT-6 Luna?
On the Artificial Analysis Intelligence Index, Nemotron 3.5 Super VL scores 13.6 and GPT-6 Luna scores 27.8, putting GPT-6 Luna ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Nemotron 3.5 Super VL and GPT-6 Luna at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Nemotron 3.5 Super VL and GPT-6 Luna answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Nemotron 3.5 Super VL and GPT-6 Luna at the same time. Compare the answers side by side and keep the best one.