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Nemotron 3.5 Super VL (120B A12B) vs Sarvam-30B

Nemotron 3.5 Super VL (120B A12B) leads the LLM Stats Score 35.0 to 19.2.

NVIDIA · Sarvam AI · Updated for 2026

Which is better?

Nemotron 3.5 Super VL (120B A12B) leads the overall LLM Stats Score 35.0 to 19.2, ranking #108 overall.

In the 4 individual benchmarks reported for both models, Nemotron 3.5 Super VL (120B A12B) wins 4; this is a narrower head-to-head signal than the composite indexes.

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

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 4 of 4 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose Sarvam-30B

  • you are already invested in the Sarvam AI ecosystem

At a glance

The differences that matter most.

Nemotron 3.5 Super VL (120B A12B)
NVIDIA
Sarvam-30B
Sarvam AI
Core performance indexes
LLM Stats Score
35.0
#108
19.2
#226
Reasoning
36.2
#94
19.0
#224
Coding
21.0
#108
5.7
#215
Agents
16.5
#99
-1.6
#201
Cost, coverage & limits
Benchmark wins
4 of 4
0 of 4
Input price
$0.20 / M
— / M
Output price
$1.00 / M
— / M
Context window
262,144
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Nemotron 3.5 Super VL (120B A12B)
Sarvam-30B
Math
28.1#101
23.5#136
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for Nemotron 3.5 Super VL (120B A12B) · 14 for Sarvam-30B

4 shared

Nemotron 3.5 Super VL (120B A12B) outperforms in 4 benchmarks (BrowseComp, GPQA, LiveCodeBench v6, SWE-Bench Verified), while Sarvam-30B is better at 0 benchmarks.

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

Tue Oct 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

90.0B diff

Nemotron 3.5 Super VL (120B A12B) has 90.0B more parameters than Sarvam-30B, making it 300.0% larger.

NVIDIA
Nemotron 3.5 Super VL (120B A12B)
120.0Bparameters
Sarvam AI
Sarvam-30B
30.0Bparameters
120.0B
Nemotron 3.5 Super VL (120B A12B)
30.0B
Sarvam-30B

Context Window

Maximum input and output token capacity

Only Nemotron 3.5 Super VL (120B A12B) specifies input context (262,144 tokens). Only Nemotron 3.5 Super VL (120B A12B) specifies output context (262,144 tokens).

NVIDIA
Nemotron 3.5 Super VL (120B A12B)
Input262,144 tokens
Output262,144 tokens
Sarvam AI
Sarvam-30B
Input- tokens
Output- tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Nemotron 3.5 Super VL (120B A12B) supports multimodal inputs, whereas Sarvam-30B 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.

Nemotron 3.5 Super VL (120B A12B)

Text
Images
Audio
Video

Sarvam-30B

Text
Images
Audio
Video

License

Usage and distribution terms

Nemotron 3.5 Super VL (120B A12B) is licensed under OpenMDW License v1.1, while Sarvam-30B uses Apache 2.0.

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

Nemotron 3.5 Super VL (120B A12B)

OpenMDW License v1.1

Open weights

Sarvam-30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Nemotron 3.5 Super VL (120B A12B) was released on 2026-10-15, while Sarvam-30B was released on 2026-03-06.

Nemotron 3.5 Super VL (120B A12B) is 7 months newer than Sarvam-30B.

Nemotron 3.5 Super VL (120B A12B)

Oct 15, 2026

2 days ago

7mo newer
Sarvam-30B

Mar 6, 2026

7 months ago

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

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Nemotron 3.5 Super VL (120B A12B) and Sarvam-30B side-by-side, then vote on the output you prefer.

Nemotron 3.5 Super VL (120B A12B)
✓ Preferred
Sarvam-30B
Open in Playground

FAQ

Common questions about Nemotron 3.5 Super VL (120B A12B) vs Sarvam-30B.

Which is better, Nemotron 3.5 Super VL (120B A12B) or Sarvam-30B?

Nemotron 3.5 Super VL (120B A12B) leads the LLM Stats Score 35.0 to 19.2. Nemotron 3.5 Super VL (120B A12B) is made by NVIDIA and Sarvam-30B is made by Sarvam AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Nemotron 3.5 Super VL (120B A12B) compare to Sarvam-30B in benchmarks?

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%. Sarvam-30B scores MATH-500: 97.0%, AIME 2025: 96.7%, MBPP: 92.7%, HumanEval: 92.1%, MMLU: 85.1%.

What are the context window sizes for Nemotron 3.5 Super VL (120B A12B) and Sarvam-30B?

Nemotron 3.5 Super VL (120B A12B) supports 262K tokens and Sarvam-30B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Nemotron 3.5 Super VL (120B A12B) and Sarvam-30B?

Key differences include LLM Stats Score (35.0 vs 19.2), multimodal support (yes vs no), licensing (OpenMDW License v1.1 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Nemotron 3.5 Super VL (120B A12B) and Sarvam-30B?

Nemotron 3.5 Super VL (120B A12B) is developed by NVIDIA and Sarvam-30B is developed by Sarvam AI.

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