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Llama 3.3 70B Instruct vs GPT-5.2-Codex

Detailed technical comparison between Llama 3.3 70B Instruct (Meta) 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

Llama 3.3 70B Instruct: 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

Llama 3.3 70B Instruct

$0.13 / MTok
Metaactive

Llama 3.3 70B Instruct

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...

View Llama 3.3 70B Instruct 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
SpecificationLlama 3.3 70B InstructGPT-5.2-Codex
ProviderMetaOpenAI
Context Window131,072 tokens400,000 tokens๐Ÿ†
Agent SuitabilityNot yet benchmarkedNot yet benchmarked
Time to First Token (TTFT)No public TTFT dataNo public TTFT data
Deployment Modelself hostablemanaged api
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2024-12-062026-01-14

API Pricing Comparison

Input Price per Million Tokens

Llama 3.3 70B Instruct

$0.13

GPT-5.2-Codex

$1.75

Output Price per Million Tokens

Llama 3.3 70B Instruct

$0.40

GPT-5.2-Codex

$14.00

๐Ÿ’ก Cost Ratio: Llama 3.3 70B Instruct is 13.5x 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
87.0%vs93.0%+6.0% GPT-5.2-Codex
Llama 3.3 70B Instruct
GPT-5.2-Codex ๐Ÿ†
HumanEvalPython coding & logic synthesis
86.2%vs99.0%+12.8% GPT-5.2-Codex
Llama 3.3 70B Instruct
GPT-5.2-Codex ๐Ÿ†
MATHComplex mathematical problem solving
67.4%vs81.4%+14.0% GPT-5.2-Codex
Llama 3.3 70B Instruct
GPT-5.2-Codex ๐Ÿ†
GPQAGraduate-level expert reasoning
48.8%vs56.4%+7.6% GPT-5.2-Codex
Llama 3.3 70B Instruct
GPT-5.2-Codex ๐Ÿ†
HellaSwagCommonsense reasoning and inference
88.0%vs88.6%+0.6% GPT-5.2-Codex
Llama 3.3 70B Instruct
GPT-5.2-Codex ๐Ÿ†
MT-BenchMulti-turn conversation flow quality
9.1%vs9.5%+0.4% GPT-5.2-Codex
Llama 3.3 70B Instruct
GPT-5.2-Codex ๐Ÿ†

Llama 3.3 70B Instruct Quirks & Gotchas

No developer gotchas reported.

GPT-5.2-Codex Quirks & Gotchas

No developer gotchas reported.

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