Kimi K3.1 Pro vs Qwen2.5-Coder 32B Instruct
Kimi K3.1 Pro leads the LLM Stats Score 55.5 to 1.6. Qwen2.5-Coder 32B Instruct is 44.4x cheaper per token.
Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Kimi K3.1 Pro leads the overall LLM Stats Score 55.5 to 1.6, ranking #5 overall.
On price, Qwen2.5-Coder 32B Instruct is roughly 44.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K3.1 Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Kimi K3.1 Pro
- overall performance matters — it scores 55.5 and ranks #5 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
Choose Qwen2.5-Coder 32B Instruct
- cost matters — it's about 44.4x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
30 reported for Kimi K3.1 Pro · 15 for Qwen2.5-Coder 32B Instruct
Kimi K3.1 Pro and Qwen2.5-Coder 32B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K3.1 Pro ($2.00/1M tokens) is 22.2x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, Kimi K3.1 Pro ($10.00/1M tokens) is 111.1x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, Kimi K3.1 Pro is more expensive than Qwen2.5-Coder 32B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Kimi K3.1 Pro accepts 1,048,576 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Kimi K3.1 Pro can generate longer responses up to 1,048,576 tokens, while Qwen2.5-Coder 32B Instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Kimi K3.1 Pro supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
Kimi K3.1 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K3.1 Pro
Qwen2.5-Coder 32B Instruct
Release Timeline
When each model was launched
Kimi K3.1 Pro was released on 2026-10-23, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
Kimi K3.1 Pro is 25 months newer than Qwen2.5-Coder 32B Instruct.
Oct 23, 2026
4 days ago
2.1yr newerSep 19, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K3.1 Pro is available from Moonshot AI. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
Kimi K3.1 Pro
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K3.1 Pro and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K3.1 Pro vs Qwen2.5-Coder 32B Instruct.