The AI arena is free today

Open Superagent

Devstral Small 1.1 vs Qwen2.5 14B Instruct

Comparing Devstral Small 1.1 and Qwen2.5 14B Instruct across benchmarks, pricing, and capabilities.

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

Which is better?

Devstral Small 1.1 and Qwen2.5 14B Instruct 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 Devstral Small 1.1

  • you want the most recent training data — it shipped Jul 2025

Choose Qwen2.5 14B Instruct

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

At a glance

The differences that matter most.

Devstral Small 1.1
Mistral AI
Qwen2.5 14B Instruct
Alibaba Cloud / Qwen Team
Benchmark wins
—
—
Input price
$0.10 / M
— / M
Output price
$0.30 / M
— / M
Context window
128,000
—
Released
Jul 2025
Sep 2024
License
Apache 2.0
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Devstral Small 1.1 and Qwen2.5 14B Instructdon'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

9.3B diff

Devstral Small 1.1 has 9.3B more parameters than Qwen2.5 14B Instruct, making it 63.3% larger.

Mistral AI
Devstral Small 1.1
24.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 14B Instruct
14.7Bparameters
24.0B
Devstral Small 1.1
14.7B
Qwen2.5 14B Instruct

Context Window

Maximum input and output token capacity

Only Devstral Small 1.1 specifies input context (128,000 tokens). Only Devstral Small 1.1 specifies output context (128,000 tokens).

Mistral AI
Devstral Small 1.1
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 14B Instruct
Input- tokens
Output- tokens
Wed Aug 26 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Devstral Small 1.1

Apache 2.0

Open weights

Qwen2.5 14B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Devstral Small 1.1 was released on 2025-07-11, while Qwen2.5 14B Instruct was released on 2024-09-19.

Devstral Small 1.1 is 10 months newer than Qwen2.5 14B Instruct.

Devstral Small 1.1

Jul 11, 2025

1.1 years ago

9mo newer
Qwen2.5 14B Instruct

Sep 19, 2024

1.9 years ago

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 Devstral Small 1.1 and Qwen2.5 14B Instruct side-by-side, then vote on the output you prefer.

Devstral Small 1.1
✓ Preferred
Qwen2.5 14B Instruct
Open in Playground

FAQ

Common questions about Devstral Small 1.1 vs Qwen2.5 14B Instruct.

Which is better, Devstral Small 1.1 or Qwen2.5 14B Instruct?

Devstral Small 1.1 (Mistral AI) and Qwen2.5 14B Instruct (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 Devstral Small 1.1 compare to Qwen2.5 14B Instruct in benchmarks?

Devstral Small 1.1 scores SWE-Bench Verified: 53.6%. Qwen2.5 14B Instruct scores GSM8k: 94.8%, HumanEval: 83.5%, MBPP: 82.0%, MATH: 80.0%, MMLU-Redux: 80.0%.

What are the context window sizes for Devstral Small 1.1 and Qwen2.5 14B Instruct?

Devstral Small 1.1 supports 128K tokens and Qwen2.5 14B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Who makes Devstral Small 1.1 and Qwen2.5 14B Instruct?

Devstral Small 1.1 is developed by Mistral AI and Qwen2.5 14B Instruct is developed by Alibaba Cloud / Qwen Team.

Related comparisons