DeepSeek-V3.2 (Thinking) vs Llama-3.3 Nemotron Super 49B v1: Specs & Benchmark Comparison
| Characteristic | DeepSeek-V3.2 (Thinking) | Llama-3.3 Nemotron Super 49B v1 |
|---|---|---|
| Company | DeepSeek | NVIDIA |
| Release Date | November 30, 2025 | March 18, 2025 |
| Parameters | 685B | 50B |
| Multimodal | No | No |
| Context (input) | 131K | — |
| Context (output) | 66K | — |
| Input Price / 1M | $0.28 | — |
| Output Price / 1M | $0.42 | — |
| Average Score | 0.9 | 0.8 |
| Benchmarks | ||
| AIME 2025 | 0.9 | 0.6 |
| GPQA | 0.8 | 0.7 |
Visual Benchmark Comparison
DeepSeek-V3.2 (Thinking)
Llama-3.3 Nemotron Super 49B v1
AIME 20250.9 vs 0.6
0.9
0.6
GPQA0.8 vs 0.7
0.8
0.7
Verdict
DeepSeek-V3.2 (Thinking) leads in 1 out of 2 comparison categories.
Overall Performance
Both models show comparable average scores: DeepSeek-V3.2 (Thinking) — 0.9, Llama-3.3 Nemotron Super 49B v1 — 0.8.
Recency
DeepSeek-V3.2 (Thinking) is newer: released 11/30/2025 vs 3/18/2025.
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Frequently Asked Questions
Which is better for coding — DeepSeek-V3.2 (Thinking) or Llama-3.3 Nemotron Super 49B v1?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — DeepSeek-V3.2 (Thinking) or Llama-3.3 Nemotron Super 49B v1?
API pricing data is available on the individual model pages.
Which has a larger context window — DeepSeek-V3.2 (Thinking) or Llama-3.3 Nemotron Super 49B v1?
Context window data is available on the individual model pages.
The DeepSeek-V3.2 (Thinking) and Llama-3.3 Nemotron Super 49B v1 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the DeepSeek-V3.2 (Thinking) or Llama-3.3 Nemotron Super 49B v1 page. See also the complete list of AI model comparisons.