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Llama-3.3 Nemotron Super 49B v1 vs Parse

Comparing Llama-3.3 Nemotron Super 49B v1 and Parse across benchmarks, pricing, and capabilities.

NVIDIA · Cohere · Updated for 2026

Which is better?

Llama-3.3 Nemotron Super 49B v1 and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose Llama-3.3 Nemotron Super 49B v1

  • you need open weights you can self-host or fine-tune

Choose Parse

  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Llama-3.3 Nemotron Super 49B v1
NVIDIA
Parse
Cohere
Benchmark wins
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—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
8,192

Individual benchmarks

7 reported for Llama-3.3 Nemotron Super 49B v1 · 1 for Parse

No common benchmarks found

Llama-3.3 Nemotron Super 49B v1 and Parsedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

47.6B diff

Llama-3.3 Nemotron Super 49B v1 has 47.6B more parameters than Parse, making it 2069.6% larger.

NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
Cohere
Parse
2.3Bparameters
49.9B
Llama-3.3 Nemotron Super 49B v1
2.3B
Parse

Context Window

Maximum input and output token capacity

Only Parse specifies input context (8,192 tokens).

NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Mon Aug 31 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Parse supports multimodal inputs, whereas Llama-3.3 Nemotron Super 49B v1 does not.

Parse can handle both text and other forms of data like images, making it suitable for multimodal applications.

Llama-3.3 Nemotron Super 49B v1

Text
Images
Audio
Video

Parse

Text
Images
Audio
Video

License

Usage and distribution terms

Llama-3.3 Nemotron Super 49B v1 is licensed under Llama 3.1 Community License, while Parse uses a proprietary license.

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

Llama-3.3 Nemotron Super 49B v1

Llama 3.1 Community License

Open weights

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18, while Parse was released on 2026-08-27.

Parse is 18 months newer than Llama-3.3 Nemotron Super 49B v1.

Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.5 years ago

Parse

Aug 27, 2026

4 days ago

1.4yr newer

Knowledge Cutoff

When training data ends

Llama-3.3 Nemotron Super 49B v1 has a documented knowledge cutoff of 2023-12-31, while Parse's cutoff date is not specified.

We can confirm Llama-3.3 Nemotron Super 49B v1's training data extends to 2023-12-31, but cannot make a direct comparison without Parse's cutoff date.

Llama-3.3 Nemotron Super 49B v1

Dec 2023

Parse

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Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Llama-3.3 Nemotron Super 49B v1 and Parse side-by-side, then vote on the output you prefer.

Llama-3.3 Nemotron Super 49B v1
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about Llama-3.3 Nemotron Super 49B v1 vs Parse.

Which is better, Llama-3.3 Nemotron Super 49B v1 or Parse?

Llama-3.3 Nemotron Super 49B v1 (NVIDIA) and Parse (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Llama-3.3 Nemotron Super 49B v1 compare to Parse in benchmarks?

Llama-3.3 Nemotron Super 49B v1 scores MATH-500: 96.6%, MT-Bench: 91.7%, MBPP: 91.3%, Arena Hard: 88.3%, BFCL v2: 73.7%. Parse scores ParseBench: 79.2%.

What are the context window sizes for Llama-3.3 Nemotron Super 49B v1 and Parse?

Llama-3.3 Nemotron Super 49B v1 supports an unknown number of tokens and Parse supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama-3.3 Nemotron Super 49B v1 and Parse?

Key differences include multimodal support (no vs yes), licensing (Llama 3.1 Community License vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama-3.3 Nemotron Super 49B v1 and Parse?

Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA and Parse is developed by Cohere.

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