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DeepSeek-V2.5 vs Nemotron 3.5 Super VL (120B A12B)

Nemotron 3.5 Super VL (120B A12B) leads the LLM Stats Score 35.0 to 7.8. DeepSeek-V2.5 is 2.3x cheaper per token.

DeepSeek · NVIDIA · Updated for 2026

Which is better?

Nemotron 3.5 Super VL (120B A12B) leads the overall LLM Stats Score 35.0 to 7.8, ranking #108 overall.

In the 1 individual benchmarks reported for both models, Nemotron 3.5 Super VL (120B A12B) wins 1; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V2.5 is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Nemotron 3.5 Super VL (120B A12B) also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V2.5

  • cost matters — it's about 2.3x cheaper per token

Choose Nemotron 3.5 Super VL (120B A12B)

  • overall performance matters — it scores 35.0 and ranks #108 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

DeepSeek-V2.5
DeepSeek
Nemotron 3.5 Super VL (120B A12B)
NVIDIA
Core performance indexes
LLM Stats Score
7.8
#305
35.0
#108
Reasoning
7.8
#301
36.2
#94
Coding
6.1
#212
21.0
#108
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
$0.14 / M
$0.20 / M
Output price
$0.28 / M
$1.00 / M
Context window
8,192
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V2.5
Nemotron 3.5 Super VL (120B A12B)
Math
14.0#232
28.1#101
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for DeepSeek-V2.5 · 19 for Nemotron 3.5 Super VL (120B A12B)

1 shared

DeepSeek-V2.5 outperforms in 0 benchmarks, while Nemotron 3.5 Super VL (120B A12B) is better at 1 benchmark (SWE-Bench Verified).

Nemotron 3.5 Super VL (120B A12B) significantly outperforms across most benchmarks.

Mon Oct 19 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

DeepSeek-V2.5 costs less

For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 1.4x cheaper than Nemotron 3.5 Super VL (120B A12B) ($0.20/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 3.6x cheaper than Nemotron 3.5 Super VL (120B A12B) ($1.00/1M tokens).

In conclusion, Nemotron 3.5 Super VL (120B A12B) is more expensive than DeepSeek-V2.5.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Oct 19 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
NVIDIA
Nemotron 3.5 Super VL (120B A12B)
Input tokens$0.20
Output tokens$1.00
Best providerDeepinfra
Notice missing or incorrect data?

Model Size

Parameter count comparison

116.0B diff

DeepSeek-V2.5 has 116.0B more parameters than Nemotron 3.5 Super VL (120B A12B), making it 96.7% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
NVIDIA
Nemotron 3.5 Super VL (120B A12B)
120.0Bparameters
236.0B
DeepSeek-V2.5
120.0B
Nemotron 3.5 Super VL (120B A12B)

Context Window

Maximum input and output token capacity

Nemotron 3.5 Super VL (120B A12B) accepts 262,144 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Nemotron 3.5 Super VL (120B A12B) can generate longer responses up to 262,144 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
NVIDIA
Nemotron 3.5 Super VL (120B A12B)
Input262,144 tokens
Output262,144 tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Nemotron 3.5 Super VL (120B A12B) supports multimodal inputs, whereas DeepSeek-V2.5 does not.

Nemotron 3.5 Super VL (120B A12B) can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V2.5

Text
Images
Audio
Video

Nemotron 3.5 Super VL (120B A12B)

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while Nemotron 3.5 Super VL (120B A12B) uses OpenMDW License v1.1.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V2.5

deepseek

Open weights

Nemotron 3.5 Super VL (120B A12B)

OpenMDW License v1.1

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Nemotron 3.5 Super VL (120B A12B) was released on 2026-10-15.

Nemotron 3.5 Super VL (120B A12B) is 30 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.4 years ago

Nemotron 3.5 Super VL (120B A12B)

Oct 15, 2026

2 days ago

2.4yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Nemotron 3.5 Super VL (120B A12B) is available from DeepInfra.

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

Nemotron 3.5 Super VL (120B A12B)

deepinfra logo
Deepinfra
Input Price:Input: $0.20/1MOutput Price:Output: $1.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V2.5 and Nemotron 3.5 Super VL (120B A12B) side-by-side, then vote on the output you prefer.

DeepSeek-V2.5
✓ Preferred
Nemotron 3.5 Super VL (120B A12B)
Open in Playground

FAQ

Common questions about DeepSeek-V2.5 vs Nemotron 3.5 Super VL (120B A12B).

Which is better, DeepSeek-V2.5 or Nemotron 3.5 Super VL (120B A12B)?

Nemotron 3.5 Super VL (120B A12B) leads the LLM Stats Score 35.0 to 7.8. DeepSeek-V2.5 is made by DeepSeek and Nemotron 3.5 Super VL (120B A12B) is made by NVIDIA. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V2.5 compare to Nemotron 3.5 Super VL (120B A12B) in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Nemotron 3.5 Super VL (120B A12B) scores GPQA: 89.5%, LiveCodeBench v6: 88.2%, CharXiv-R: 80.8%, MathVision: 78.2%, BrowseComp: 78.0%.

Is DeepSeek-V2.5 cheaper than Nemotron 3.5 Super VL (120B A12B)?

DeepSeek-V2.5 is 1.4x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. Nemotron 3.5 Super VL (120B A12B) costs $0.20/M input and $1.00/M output via deepinfra.

What are the context window sizes for DeepSeek-V2.5 and Nemotron 3.5 Super VL (120B A12B)?

DeepSeek-V2.5 supports 8K tokens and Nemotron 3.5 Super VL (120B A12B) supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V2.5 and Nemotron 3.5 Super VL (120B A12B)?

Key differences include LLM Stats Score (7.8 vs 35.0), context window (8K vs 262K), input pricing ($0.14 vs $0.20/M), multimodal support (no vs yes), licensing (deepseek vs OpenMDW License v1.1). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V2.5 and Nemotron 3.5 Super VL (120B A12B)?

DeepSeek-V2.5 is developed by DeepSeek and Nemotron 3.5 Super VL (120B A12B) is developed by NVIDIA.

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