โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Laguna M.1 vs GPT-5.2-Codex

Detailed technical comparison between Laguna M.1 (Poolside) 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

Laguna M.1: 0 WinsvsGPT-5.2-Codex: 6 Wins
Context Leader

GPT-5.2-Codex

400,000 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

Laguna M.1

$0.20 / MTok
Poolsideactive

Laguna M.1

Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai/), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 256K...

View Laguna M.1 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
SpecificationLaguna M.1GPT-5.2-Codex
ProviderPoolsideOpenAI
Context Window262,144 tokens400,000 tokens๐Ÿ†
Agent SuitabilityNot yet benchmarkedNot yet benchmarked
Time to First Token (TTFT)No public TTFT dataNo public TTFT data
Deployment Modelmanaged apimanaged api
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2026-04-282026-01-14

API Pricing Comparison

Input Price per Million Tokens

Laguna M.1

$0.20

GPT-5.2-Codex

$1.75

Output Price per Million Tokens

Laguna M.1

$0.40

GPT-5.2-Codex

$14.00

๐Ÿ’ก Cost Ratio: Laguna M.1 is 8.8x 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
81.2%vs93.0%+11.8% GPT-5.2-Codex
Laguna M.1
GPT-5.2-Codex ๐Ÿ†
HumanEvalPython coding & logic synthesis
79.4%vs99.0%+19.6% GPT-5.2-Codex
Laguna M.1
GPT-5.2-Codex ๐Ÿ†
MATHComplex mathematical problem solving
56.6%vs81.4%+24.8% GPT-5.2-Codex
Laguna M.1
GPT-5.2-Codex ๐Ÿ†
GPQAGraduate-level expert reasoning
38.6%vs56.4%+17.8% GPT-5.2-Codex
Laguna M.1
GPT-5.2-Codex ๐Ÿ†
HellaSwagCommonsense reasoning and inference
80.8%vs88.6%+7.8% GPT-5.2-Codex
Laguna M.1
GPT-5.2-Codex ๐Ÿ†
MT-BenchMulti-turn conversation flow quality
8.3%vs9.5%+1.1% GPT-5.2-Codex
Laguna M.1
GPT-5.2-Codex ๐Ÿ†

Laguna M.1 Quirks & Gotchas

No developer gotchas reported.

GPT-5.2-Codex Quirks & Gotchas

No developer gotchas reported.

Explore Other Popular Comparisons