Model Comparison

Qwen3.5-397B-A17B vs Llama 3.1 Nemotron 70B Instruct

Comparing Qwen3.5-397B-A17B and Llama 3.1 Nemotron 70B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Qwen3.5-397B-A17B and Llama 3.1 Nemotron 70B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers

Fri Apr 17 2026 • llm-stats.com

Qwen3.5-397B-A17B

Input tokens$0.60

Output tokens$3.60

Best providerNovita

Llama 3.1 Nemotron 70B Instruct

Input tokens$0.00

Output tokens$0.00

Best providerUnknown Organization

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

327.0B diff

Qwen3.5-397B-A17B has 327.0B more parameters than Llama 3.1 Nemotron 70B Instruct, making it 467.1% larger.

Qwen3.5-397B-A17B

397.0Bparameters

Llama 3.1 Nemotron 70B Instruct

70.0Bparameters

397.0B

Qwen3.5-397B-A17B

70.0B

Llama 3.1 Nemotron 70B Instruct

Context Window

Maximum input and output token capacity

Only Qwen3.5-397B-A17B specifies input context (262,144 tokens). Only Qwen3.5-397B-A17B specifies output context (64,000 tokens).

Qwen3.5-397B-A17B

Input262,144 tokens

Output64,000 tokens

Llama 3.1 Nemotron 70B Instruct

Input- tokens

Output- tokens

Fri Apr 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.5-397B-A17B supports multimodal inputs, whereas Llama 3.1 Nemotron 70B Instruct does not.

Qwen3.5-397B-A17B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen3.5-397B-A17B

Text

Images

Audio

Video

Llama 3.1 Nemotron 70B Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

Qwen3.5-397B-A17B is licensed under Apache 2.0, while Llama 3.1 Nemotron 70B Instruct uses Llama 3.1 Community License.

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

Qwen3.5-397B-A17B

Apache 2.0

Open weights

Llama 3.1 Nemotron 70B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while Llama 3.1 Nemotron 70B Instruct was released on 2024-10-01.

Qwen3.5-397B-A17B is 17 months newer than Llama 3.1 Nemotron 70B Instruct.

Qwen3.5-397B-A17B

Feb 16, 2026

2 months ago

1.4yr newer

Llama 3.1 Nemotron 70B Instruct

Oct 1, 2024

1.5 years ago

Knowledge Cutoff

When training data ends

Llama 3.1 Nemotron 70B Instruct has a documented knowledge cutoff of 2023-12-01, while Qwen3.5-397B-A17B's cutoff date is not specified.

We can confirm Llama 3.1 Nemotron 70B Instruct's training data extends to 2023-12-01, but cannot make a direct comparison without Qwen3.5-397B-A17B's cutoff date.

Qwen3.5-397B-A17B

—

Llama 3.1 Nemotron 70B Instruct

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Qwen3.5-397B-A17B

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Supports multimodal inputs

Llama 3.1 Nemotron 70B Instruct

View details

NVIDIA

Detailed Comparison

AI Model Comparison Table
Feature	Qwen3.5-397B-A17B	Llama 3.1 Nemotron 70B Instruct

FAQ

Common questions about Qwen3.5-397B-A17B vs Llama 3.1 Nemotron 70B Instruct

Qwen3.5-397B-A17B (Alibaba Cloud / Qwen Team) and Llama 3.1 Nemotron 70B Instruct (NVIDIA) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

Qwen3.5-397B-A17B scores MMLU-Redux: 94.9%, HMMT 2025: 94.8%, C-Eval: 93.0%, HMMT25: 92.7%, IFEval: 92.6%. Llama 3.1 Nemotron 70B Instruct scores GSM8k: 91.4%, HellaSwag: 85.6%, Winogrande: 84.5%, GSM8K Chat: 81.9%, MMLU Chat: 80.6%.

Qwen3.5-397B-A17B supports 262K tokens and Llama 3.1 Nemotron 70B Instruct 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 multimodal support (yes vs no), licensing (Apache 2.0 vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Qwen3.5-397B-A17B is developed by Alibaba Cloud / Qwen Team and Llama 3.1 Nemotron 70B Instruct is developed by NVIDIA.

Qwen3.5-397B-A17B vs Llama 3.1 Nemotron 70B Instruct

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

Input Capabilities

Qwen3.5-397B-A17B

Llama 3.1 Nemotron 70B Instruct

License

Release Timeline

Knowledge Cutoff

Outputs Comparison

Key Takeaways

Qwen3.5-397B-A17B

Llama 3.1 Nemotron 70B Instruct

Detailed Comparison

FAQ

Which is better, Qwen3.5-397B-A17B or Llama 3.1 Nemotron 70B Instruct?

How does Qwen3.5-397B-A17B compare to Llama 3.1 Nemotron 70B Instruct in benchmarks?

What are the context window sizes for Qwen3.5-397B-A17B and Llama 3.1 Nemotron 70B Instruct?

What are the main differences between Qwen3.5-397B-A17B and Llama 3.1 Nemotron 70B Instruct?

Who makes Qwen3.5-397B-A17B and Llama 3.1 Nemotron 70B Instruct?