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MiniMax M2.7 vs Mixtral 8x22B Instruct

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 MiniMax M2.7 and Mixtral 8x22B Instruct.

MiniMax

MiniMax M2.7

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...

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Mistral

Mixtral 8x22B Instruct

Mistral's official instruct fine-tuned version of [Mixtral 8x22B](/models/mistralai/mixtral-8x22b). It uses 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. Its strengths include: - strong math, coding,...

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Technical Specifications

SpecificationMiniMax M2.7Mixtral 8x22B Instruct
ProviderMiniMaxMistral
Context Window204,800 tokens65,536 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-03-182024-04-17

API Pricing Comparison

Input Price per Million Tokens

MiniMax M2.7

$0.18

Mixtral 8x22B Instruct

$2.00

Output Price per Million Tokens

MiniMax M2.7

$0.72

Mixtral 8x22B Instruct

$6.00

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
MiniMax M2.7
Mixtral 8x22B Instruct
HumanEvalPython coding & logic synthesis
8000.0%vsN/A
MiniMax M2.7
Mixtral 8x22B Instruct
MATHComplex mathematical problem solving
5400.0%vsN/A
MiniMax M2.7
Mixtral 8x22B Instruct
GPQAGraduate-level expert reasoning
3900.0%vsN/A
MiniMax M2.7
Mixtral 8x22B Instruct
HellaSwagCommonsense reasoning and inference
8400.0%vsN/A
MiniMax M2.7
Mixtral 8x22B Instruct
MT-BenchMulti-turn conversation flow quality
870.0%vsN/A
MiniMax M2.7
Mixtral 8x22B Instruct

MiniMax M2.7 Quirks & Gotchas

No developer gotchas reported.

Mixtral 8x22B Instruct Quirks & Gotchas

No developer gotchas reported.