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Kimi K2.6 vs Qwen 2.5 72B

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Kimi K2.6 and Qwen 2.5 72B.

Moonshot AI

Kimi K2.6

Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and...

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Alibaba

Qwen 2.5 72B

Qwen 2.5 72B is Alibaba Cloud's flagship open-weight large language model from the Qwen 2.5 generation, delivering GPT-4-class performance across general reasoning, coding, mathematics, and multilingual tasks with strong Chinese-language superiority. It supports a 131,072-token context window and is available under a permissive Apache 2.0 license for both research and commercial use, making it one of the most popular open-weight alternatives to Llama for bilingual applications.

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Technical Specifications

SpecificationKimi K2.6Qwen 2.5 72B
ProviderMoonshot AIAlibaba
Context Window262,144 tokens131,072 tokens
Agent SuitabilityN/A88/100
Time to First Token (TTFT)N/A280 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202025-09-19

API Pricing Comparison

Input Price per Million Tokens

Kimi K2.6

$0.66

Qwen 2.5 72B

$0.40

Output Price per Million Tokens

Kimi K2.6

$3.41

Qwen 2.5 72B

$0.80

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
8420.0%vsN/A
Kimi K2.6
Qwen 2.5 72B
HumanEvalPython coding & logic synthesis
8500.0%vsN/A
Kimi K2.6
Qwen 2.5 72B
MATHComplex mathematical problem solving
6400.0%vsN/A
Kimi K2.6
Qwen 2.5 72B
GPQAGraduate-level expert reasoning
4300.0%vsN/A
Kimi K2.6
Qwen 2.5 72B
HellaSwagCommonsense reasoning and inference
8500.0%vsN/A
Kimi K2.6
Qwen 2.5 72B
MT-BenchMulti-turn conversation flow quality
890.0%vsN/A
Kimi K2.6
Qwen 2.5 72B

Kimi K2.6 Quirks & Gotchas

No developer gotchas reported.

Qwen 2.5 72B Quirks & Gotchas

  • โ–ธStrong bilingual (ZH/EN) performance โ€” best open model for Chinese-language tasks
  • โ–ธSelf-hostable via vLLM or Ollama with 4-bit quantization