AI model comparison
Nemotron 3.5 Super VL vs DeepSeek V3.2
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
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
- $0.10
- Output / 1M
- $0.40
- Context
- 1.05M
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance.
- Input / 1M
- $0.28
- Output / 1M
- $0.42
- Context
- 164K
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
Nemotron 3.5 Super VL
1.9x cheaper for a typical chat
Higher intelligence score
Nemotron 3.5 Super VL
26.5 vs 21.5 on Artificial Analysis
Larger context window
Nemotron 3.5 Super VL
1.05M vs 164K 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
DeepSeek V3.221.5Coding index
DeepSeek V3.244.2Agentic index
DeepSeek V3.2Not availablePricing
Nemotron 3.5 Super VL vs DeepSeek V3.2 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | DeepSeek V3.2 | |
|---|---|---|
| Input tokensPer 1M tokens | $0.10 | $0.28 |
| Output tokensPer 1M tokens | $0.40 | $0.42 |
| Cached input (read)Per 1M tokens | $0.08 | $0.03 |
| Cache writePer 1M tokens | Not available | Not available |
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
DeepSeek V3.2$0.77Coding task
30K in, 4K out
DeepSeek V3.2$10.08$2.52 cachedLong document summary
150K in, 2K out
DeepSeek V3.2$42.84$5.04 cachedSpecs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | DeepSeek V3.2 | |
|---|---|---|
| Context window | 1.05M tokens | 164K tokens |
| Max output | 236K tokens | 66K tokens |
| Input types | Image, Text, Video | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | October 15, 2026 | December 1, 2025 |
Features
Supported features
API features available for each model.
| Metric | DeepSeek V3.2 | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not 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 DeepSeek V4 Pro 0423
- Nemotron 3.5 Super VL vs MiniMax M3
- Nemotron 3.5 Super VL vs Solar Pro 4
- Nemotron 3.5 Super VL vs MiMo-V2.5-Pro
- Nemotron 3.5 Super VL vs Hy3
- Nemotron 3.5 Super VL vs DeepSeek V4.1 Flash
- Nemotron 3.5 Super VL vs Ling 3.0 Flash VL
- Nemotron 3.5 Super VL vs DeepSeek V4 Flash 0423
- Nemotron 3.5 Super VL vs Solar Mini 4
- Nemotron 3.5 Super VL vs MiMo-V2.5
DeepSeek V3.2View full model details- DeepSeek V3.2 vs DeepSeek V4.1 Flash
- DeepSeek V3.2 vs Hy3
- DeepSeek V3.2 vs DeepSeek V4 Flash 0423
- DeepSeek V3.2 vs Solar Mini 4
- DeepSeek V3.2 vs Qwen3.6 35B A3B
- DeepSeek V3.2 vs DeepSeek V4 Pro 0423
- DeepSeek V3.2 vs MiMo-V2.5
- DeepSeek V3.2 vs Ling 3.0 Flash
- DeepSeek V3.2 vs GPT-5.4 Nano
- DeepSeek V3.2 vs Ling 3.0 Flash VL
- DeepSeek V3.2 vs MiniMax M2.5
- DeepSeek V3.2 vs Step 3.5 Flash
- DeepSeek V3.2 vs DeepSeek V3.2 Exp
Our take
Nemotron 3.5 Super VL is 1.9x cheaper for a typical chat. Nemotron 3.5 Super VL scores higher on the Artificial Analysis Intelligence Index (26.5 vs 21.5). Nemotron 3.5 Super VL has the larger context window (1.05M vs 164K 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 DeepSeek V3.2 cheaper?
Nemotron 3.5 Super VL is cheaper for a typical chat (2K input tokens and 500 output tokens). Nemotron 3.5 Super VL costs $0.10 per 1M input tokens and $0.40 per 1M output tokens, while DeepSeek V3.2 costs $0.28 per 1M input tokens and $0.42 per 1M output tokens.
Which has a bigger context window, Nemotron 3.5 Super VL or DeepSeek V3.2?
Nemotron 3.5 Super VL supports up to 1.05M tokens of context, compared with 164K for DeepSeek V3.2.
Is Nemotron 3.5 Super VL smarter than DeepSeek V3.2?
On the Artificial Analysis Intelligence Index, Nemotron 3.5 Super VL scores 26.5 and DeepSeek V3.2 scores 21.5, putting Nemotron 3.5 Super VL 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 DeepSeek V3.2 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 DeepSeek V3.2 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Nemotron 3.5 Super VL and DeepSeek V3.2 at the same time. Compare the answers side by side and keep the best one.