Model Comparison

Jamba 1.5 Large vs Llama-3.3 Nemotron Super 49B v1

Llama-3.3 Nemotron Super 49B v1 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Jamba 1.5 Large outperforms in 0 benchmarks, while Llama-3.3 Nemotron Super 49B v1 is better at 2 benchmarks (Arena Hard, GPQA).

Llama-3.3 Nemotron Super 49B v1 significantly outperforms across most benchmarks.

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
AI21 Labs
Jamba 1.5 Large
Input tokens$2.00
Output tokens$8.00
Best providerAWS Bedrock
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

348.1B diff

Jamba 1.5 Large has 348.1B more parameters than Llama-3.3 Nemotron Super 49B v1, making it 697.6% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
NVIDIA
Llama-3.3 Nemotron Super 49B v1
49.9Bparameters
398.0B
Jamba 1.5 Large
49.9B
Llama-3.3 Nemotron Super 49B v1

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Large specifies input context (256,000 tokens). Only Jamba 1.5 Large specifies output context (256,000 tokens).

AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
NVIDIA
Llama-3.3 Nemotron Super 49B v1
Input- tokens
Output- tokens
Thu Apr 16 2026 • llm-stats.com

License

Usage and distribution terms

Jamba 1.5 Large is licensed under Jamba Open Model License, while Llama-3.3 Nemotron Super 49B v1 uses Llama 3.1 Community License.

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

Jamba 1.5 Large

Jamba Open Model License

Open weights

Llama-3.3 Nemotron Super 49B v1

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

Jamba 1.5 Large was released on 2024-08-22, while Llama-3.3 Nemotron Super 49B v1 was released on 2025-03-18.

Llama-3.3 Nemotron Super 49B v1 is 7 months newer than Jamba 1.5 Large.

Jamba 1.5 Large

Aug 22, 2024

1.6 years ago

Llama-3.3 Nemotron Super 49B v1

Mar 18, 2025

1.1 years ago

6mo newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a knowledge cutoff of 2024-03-05, while Llama-3.3 Nemotron Super 49B v1 has a cutoff of 2023-12-31.

Jamba 1.5 Large has more recent training data (up to 2024-03-05), making it potentially better informed about events through that date compared to Llama-3.3 Nemotron Super 49B v1 (2023-12-31).

Jamba 1.5 Large

Mar 2024

3 mo newer
Llama-3.3 Nemotron Super 49B v1

Dec 2023

Outputs Comparison

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Key Takeaways

AI21 Labs
Larger context window (256,000 tokens)
NVIDIA
Higher Arena Hard score (88.3% vs 65.4%)
Higher GPQA score (66.7% vs 36.9%)

Detailed Comparison

AI Model Comparison Table
Feature
AI21 Labs
Jamba 1.5 Large
NVIDIA
Llama-3.3 Nemotron Super 49B v1

FAQ

Common questions about Jamba 1.5 Large vs Llama-3.3 Nemotron Super 49B v1

Llama-3.3 Nemotron Super 49B v1 significantly outperforms across most benchmarks. Jamba 1.5 Large is made by AI21 Labs and Llama-3.3 Nemotron Super 49B v1 is made by NVIDIA. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. 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%.
Jamba 1.5 Large supports 256K tokens and Llama-3.3 Nemotron Super 49B v1 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Jamba Open Model License vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.
Jamba 1.5 Large is developed by AI21 Labs and Llama-3.3 Nemotron Super 49B v1 is developed by NVIDIA.