Kimi K2.5 vs Qwen3-Next-80B-A3B-Instruct
Kimi K2.5 leads the LLM Stats Score 38.8 to 20.2. Qwen3-Next-80B-A3B-Instruct is 3.5x cheaper per token.
Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Kimi K2.5 leads the overall LLM Stats Score 38.8 to 20.2, ranking #61 overall.
In the 4 individual benchmarks reported for both models, Kimi K2.5 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3-Next-80B-A3B-Instruct is roughly 3.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3-Next-80B-A3B-Instruct also accepts a larger context window (262,144 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 K2.5
- overall performance matters — it scores 38.8 and ranks #61 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- you want the most recent training data — it shipped Jan 2026
Choose Qwen3-Next-80B-A3B-Instruct
- cost matters — it's about 3.5x cheaper per token
- you process long inputs — it offers a 262,144 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
40 reported for Kimi K2.5 · 24 for Qwen3-Next-80B-A3B-Instruct
Kimi K2.5 outperforms in 4 benchmarks (AIME 2025, GPQA, LiveCodeBench v6, MMLU-Pro), while Qwen3-Next-80B-A3B-Instruct is better at 0 benchmarks.
Kimi K2.5 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2.5 ($0.60/1M tokens) is 6.7x more expensive than Qwen3-Next-80B-A3B-Instruct ($0.09/1M tokens).
For output processing, Kimi K2.5 ($3.00/1M tokens) is 2.7x more expensive than Qwen3-Next-80B-A3B-Instruct ($1.10/1M tokens).
In conclusion, Kimi K2.5 is more expensive than Qwen3-Next-80B-A3B-Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2.5 has 920.0B more parameters than Qwen3-Next-80B-A3B-Instruct, making it 1150.0% larger.
Context Window
Maximum input and output token capacity
Qwen3-Next-80B-A3B-Instruct accepts 262,144 input tokens compared to Kimi K2.5's 262,100 tokens. Qwen3-Next-80B-A3B-Instruct can generate longer responses up to 262,144 tokens, while Kimi K2.5 is limited to 262,100 tokens.
Input capabilities
Documented input modalities across available providers
Kimi K2.5 supports multimodal inputs, whereas Qwen3-Next-80B-A3B-Instruct does not.
Kimi K2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2.5
Qwen3-Next-80B-A3B-Instruct
License
Usage and distribution terms
Kimi K2.5 is licensed under MIT, while Qwen3-Next-80B-A3B-Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Kimi K2.5 was released on 2026-01-27, while Qwen3-Next-80B-A3B-Instruct was released on 2025-09-10.
Kimi K2.5 is 5 months newer than Qwen3-Next-80B-A3B-Instruct.
Jan 27, 2026
7 months ago
4mo newerSep 10, 2025
1.0 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 K2.5 is available from Fireworks, Moonshot AI. Qwen3-Next-80B-A3B-Instruct is available from DeepInfra, Novita.
Kimi K2.5
Qwen3-Next-80B-A3B-Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.5 and Qwen3-Next-80B-A3B-Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.5 vs Qwen3-Next-80B-A3B-Instruct.