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Mistral NeMo Instruct vs Qwen3.8-Flash-Next

Comparing Mistral NeMo Instruct and Qwen3.8-Flash-Next across benchmarks, pricing, and capabilities.

Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Mistral NeMo Instruct and Qwen3.8-Flash-Next trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose Mistral NeMo Instruct

  • you want predictable pricing at $0.15/M input and $0.15/M output

Choose Qwen3.8-Flash-Next

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

At a glance

The differences that matter most.

Mistral NeMo Instruct
Mistral AI
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Benchmark wins
—
—
Input price
$0.15 / M
— / M
Output price
$0.15 / M
— / M
Context window
128,000
—
Released
Jul 2024
Aug 2026
License
Apache 2.0
Qwen Community License 1.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Mistral NeMo Instruct and Qwen3.8-Flash-Nextdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

113.0B diff

Qwen3.8-Flash-Next has 113.0B more parameters than Mistral NeMo Instruct, making it 941.7% larger.

Mistral AI
Mistral NeMo Instruct
12.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
12.0B
Mistral NeMo Instruct
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only Mistral NeMo Instruct specifies input context (128,000 tokens). Only Mistral NeMo Instruct specifies output context (128,000 tokens).

Mistral AI
Mistral NeMo Instruct
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.8-Flash-Next supports multimodal inputs, whereas Mistral NeMo Instruct does not.

Qwen3.8-Flash-Next can handle both text and other forms of data like images, making it suitable for multimodal applications.

Mistral NeMo Instruct

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

Mistral NeMo Instruct is licensed under Apache 2.0, 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.

Mistral NeMo Instruct

Apache 2.0

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

Mistral NeMo Instruct was released on 2024-07-18, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 26 months newer than Mistral NeMo Instruct.

Mistral NeMo Instruct

Jul 18, 2024

2.1 years ago

Qwen3.8-Flash-Next

Aug 26, 2026

0 days ago

2.1yr 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 Mistral NeMo Instruct and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

Mistral NeMo Instruct
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about Mistral NeMo Instruct vs Qwen3.8-Flash-Next.

Which is better, Mistral NeMo Instruct or Qwen3.8-Flash-Next?

Mistral NeMo Instruct (Mistral AI) and Qwen3.8-Flash-Next (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Mistral NeMo Instruct compare to Qwen3.8-Flash-Next in benchmarks?

Mistral NeMo Instruct scores HellaSwag: 83.5%, Winogrande: 76.8%, TriviaQA: 73.8%, CommonSenseQA: 70.4%, MMLU: 68.0%. 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 Mistral NeMo Instruct and Qwen3.8-Flash-Next?

Mistral NeMo 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 Mistral NeMo Instruct and Qwen3.8-Flash-Next?

Key differences include multimodal support (no vs yes), licensing (Apache 2.0 vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Mistral NeMo Instruct and Qwen3.8-Flash-Next?

Mistral NeMo Instruct is developed by Mistral AI and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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