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Kimi K2.5 vs Mixtral 8x22B

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 K2.5 and Mixtral 8x22B.

Moonshot AI

Kimi K2.5

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed...

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Mistral

Mixtral 8x22B

Mixtral 8x22B is Mistral AI's open-weight Mixture-of-Experts model, activating only 39B of its 141B total parameters per token to deliver frontier-level performance at inference costs comparable to a much smaller dense model. Released under the Apache 2.0 license, Mixtral 8x22B is one of the most capable fully open-weight models available, with strong multilingual performance, robust coding ability, and efficient fine-tuning via LoRA. It is widely deployed across self-hosted infrastructure, including Ollama, vLLM, and Hugging Face TGI.

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Technical Specifications

SpecificationKimi K2.5Mixtral 8x22B
ProviderMoonshot AIMistral
Context Window262,144 tokens65,536 tokens
Agent SuitabilityN/A87/100
Time to First Token (TTFT)N/A320 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-01-272024-12-11

API Pricing Comparison

Input Price per Million Tokens

Kimi K2.5

$0.38

Mixtral 8x22B

$0.50

Output Price per Million Tokens

Kimi K2.5

$2.02

Mixtral 8x22B

$1.00

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
8250.0%vsN/A
Kimi K2.5
Mixtral 8x22B
HumanEvalPython coding & logic synthesis
8300.0%vsN/A
Kimi K2.5
Mixtral 8x22B
MATHComplex mathematical problem solving
5900.0%vsN/A
Kimi K2.5
Mixtral 8x22B
GPQAGraduate-level expert reasoning
4100.0%vsN/A
Kimi K2.5
Mixtral 8x22B
HellaSwagCommonsense reasoning and inference
8400.0%vsN/A
Kimi K2.5
Mixtral 8x22B
MT-BenchMulti-turn conversation flow quality
880.0%vsN/A
Kimi K2.5
Mixtral 8x22B

Kimi K2.5 Quirks & Gotchas

No developer gotchas reported.

Mixtral 8x22B Quirks & Gotchas

  • โ–ธMoE architecture โ€” efficient inference for its capability tier
  • โ–ธRequires ~90GB VRAM at FP16 โ€” 4-bit quantization recommended for single-GPU deployment