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Llama 3.2 90B Instruct vs Qwen3.8-Flash-Next

Qwen3.8-Flash-Next significantly outperforms across most benchmarks.

Meta · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Llama 3.2 90B Instruct outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 1 benchmark (GPQA). Qwen3.8-Flash-Next significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Llama 3.2 90B Instruct

  • you want predictable pricing at $0.35/M input and $0.40/M output

Choose Qwen3.8-Flash-Next

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
0 of 1
1 of 1
Input price
$0.35 / M
— / M
Output price
$0.40 / M
— / M
Context window
128,000
Released
Sep 2024
Aug 2026
License
Llama 3.2
Qwen Community License 1.0

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Llama 3.2 90B Instruct outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 1 benchmark (GPQA).

Qwen3.8-Flash-Next significantly outperforms across most benchmarks.

Thu Aug 27 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

35.0B diff

Qwen3.8-Flash-Next has 35.0B more parameters than Llama 3.2 90B Instruct, making it 38.9% larger.

Meta
Llama 3.2 90B Instruct
90.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
90.0B
Llama 3.2 90B Instruct
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only Llama 3.2 90B Instruct specifies input context (128,000 tokens). Only Llama 3.2 90B Instruct specifies output context (128,000 tokens).

Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Thu Aug 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Llama 3.2 90B Instruct and Qwen3.8-Flash-Next support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Llama 3.2 90B Instruct

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.2 90B Instruct is licensed under Llama 3.2, while Qwen3.8-Flash-Next uses Qwen Community License 1.0.

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

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

Llama 3.2 90B Instruct was released on 2024-09-25, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 23 months newer than Llama 3.2 90B Instruct.

Llama 3.2 90B Instruct

Sep 25, 2024

1.9 years ago

Qwen3.8-Flash-Next

Aug 26, 2026

1 days ago

1.9yr 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Llama 3.2 90B Instruct and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

Llama 3.2 90B Instruct
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about Llama 3.2 90B Instruct vs Qwen3.8-Flash-Next.

Which is better, Llama 3.2 90B Instruct or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next significantly outperforms across most benchmarks. Llama 3.2 90B Instruct is made by Meta and Qwen3.8-Flash-Next is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Llama 3.2 90B Instruct compare to Qwen3.8-Flash-Next in benchmarks?

Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%. Qwen3.8-Flash-Next scores MathVision: 95.7%, LiveCodeBench v6: 91.9%, GPQA: 91.7%, CharXiv-R: 90.6%, RealWorldQA: 88.5%.

What are the context window sizes for Llama 3.2 90B Instruct and Qwen3.8-Flash-Next?

Llama 3.2 90B Instruct supports 128K tokens and Qwen3.8-Flash-Next 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 Llama 3.2 90B Instruct and Qwen3.8-Flash-Next?

Key differences include licensing (Llama 3.2 vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.2 90B Instruct and Qwen3.8-Flash-Next?

Llama 3.2 90B Instruct is developed by Meta and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.