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GPT-3.5 Turbo Instruct vs GLM 5.2

Detailed technical comparison between GPT-3.5 Turbo Instruct (OpenAI) and GLM 5.2 (Zhipu AI). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

⚡ Executive Summary & Verdict

Comparison Snapshot

GPT-3.5 Turbo Instruct: 0 WinsvsGLM 5.2: 6 Wins
Context Leader

GLM 5.2

1,048,576 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GLM 5.2

$0.80 / MTok
OpenAIactive

GPT-3.5 Turbo Instruct

This model is a variant of GPT-3.5 Turbo tuned for instructional prompts and omitting chat-related optimizations. Training data: up to Sep 2021.

View GPT-3.5 Turbo Instruct Full Specs →
Zhipu AIactive

GLM 5.2

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

View GLM 5.2 Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationGPT-3.5 Turbo InstructGLM 5.2
ProviderOpenAIZhipu AI
Context Window4,095 tokens1,048,576 tokens🏆
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablebeta
API AvailableYesYes
Released Date2023-09-282026-06-16

API Pricing Comparison

Input Price per Million Tokens

GPT-3.5 Turbo Instruct

$1.50

GLM 5.2

$0.80

Output Price per Million Tokens

GPT-3.5 Turbo Instruct

$2.00

GLM 5.2

$2.50

💡 Cost Ratio: GLM 5.2 is 1.9x cheaper per input token than GPT-3.5 Turbo Instruct.

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.

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Benchmark Performance Metrics

Standardized Scores (0–100%)

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

MMLUGeneral knowledge & multi-task understanding
79.8%vs89.5%+9.7% GLM 5.2
GPT-3.5 Turbo Instruct
GLM 5.2 🏆
HumanEvalPython coding & logic synthesis
78.0%vs91.2%+13.2% GLM 5.2
GPT-3.5 Turbo Instruct
GLM 5.2 🏆
MATHComplex mathematical problem solving
55.2%vs80.5%+25.3% GLM 5.2
GPT-3.5 Turbo Instruct
GLM 5.2 🏆
GPQAGraduate-level expert reasoning
40.6%vs53.5%+12.9% GLM 5.2
GPT-3.5 Turbo Instruct
GLM 5.2 🏆
HellaSwagCommonsense reasoning and inference
82.8%vs89.8%+7.0% GLM 5.2
GPT-3.5 Turbo Instruct
GLM 5.2 🏆
MT-BenchMulti-turn conversation flow quality
8.5%vs9.3%+0.8% GLM 5.2
GPT-3.5 Turbo Instruct
GLM 5.2 🏆

GPT-3.5 Turbo Instruct Quirks & Gotchas

No developer gotchas reported.

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

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