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MiMo-V2.5 vs GPT-5.2-Codex

Detailed technical comparison between MiMo-V2.5 (Xiaomi) and GPT-5.2-Codex (OpenAI). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

โšก Executive Summary & Verdict

Comparison Snapshot

MiMo-V2.5: 0 WinsvsGPT-5.2-Codex: 6 Wins
Context Leader

MiMo-V2.5

1,050,000 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

MiMo-V2.5

$0.14 / MTok
Xiaomiactive

MiMo-V2.5

MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...

View MiMo-V2.5 Full Specs โ†’
OpenAIactive

GPT-5.2-Codex

GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....

View GPT-5.2-Codex Full Specs โ†’

Technical Specifications

๐Ÿ† = Superior Spec
SpecificationMiMo-V2.5GPT-5.2-Codex
ProviderXiaomiOpenAI
Context Window1,050,000 tokens๐Ÿ†400,000 tokens
Agent SuitabilityNot yet benchmarkedNot yet benchmarked
Time to First Token (TTFT)No public TTFT dataNo public TTFT data
Deployment Modelmanaged apimanaged api
Production StabilityBeta Access (est.)Stable GA (est.)
API AvailableYesYes
Released Date2026-04-222026-01-14

API Pricing Comparison

Input Price per Million Tokens

MiMo-V2.5

$0.14

GPT-5.2-Codex

$1.75

Output Price per Million Tokens

MiMo-V2.5

$0.28

GPT-5.2-Codex

$14.00

๐Ÿ’ก Cost Ratio: MiMo-V2.5 is 12.5x cheaper per input token than GPT-5.2-Codex.

Want to test both models live?

Run side-by-side prompt benchmarks in our dynamic multi-model Sandbox. Compare execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Standardized Scores (0โ€“100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
81.4%vs93.0%+11.6% GPT-5.2-Codex
MiMo-V2.5
GPT-5.2-Codex ๐Ÿ†
HumanEvalPython coding & logic synthesis
79.6%vs99.0%+19.4% GPT-5.2-Codex
MiMo-V2.5
GPT-5.2-Codex ๐Ÿ†
MATHComplex mathematical problem solving
53.4%vs81.4%+28.0% GPT-5.2-Codex
MiMo-V2.5
GPT-5.2-Codex ๐Ÿ†
GPQAGraduate-level expert reasoning
38.8%vs56.4%+17.6% GPT-5.2-Codex
MiMo-V2.5
GPT-5.2-Codex ๐Ÿ†
HellaSwagCommonsense reasoning and inference
81.0%vs88.6%+7.6% GPT-5.2-Codex
MiMo-V2.5
GPT-5.2-Codex ๐Ÿ†
MT-BenchMulti-turn conversation flow quality
8.4%vs9.5%+1.1% GPT-5.2-Codex
MiMo-V2.5
GPT-5.2-Codex ๐Ÿ†

MiMo-V2.5 Quirks & Gotchas

No developer gotchas reported.

GPT-5.2-Codex Quirks & Gotchas

No developer gotchas reported.

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