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GPT-3.5 Turbo 16k vs GLM 5.2

Detailed technical comparison between GPT-3.5 Turbo 16k (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 16k: 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 16k

This model offers four times the context length of gpt-3.5-turbo, allowing it to support approximately 20 pages of text in a single request at a higher cost. Training data: up...

View GPT-3.5 Turbo 16k 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 16kGLM 5.2
ProviderOpenAIZhipu AI
Context Window16,385 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 Date2023-08-282026-06-16

API Pricing Comparison

Input Price per Million Tokens

GPT-3.5 Turbo 16k

$3.00

GLM 5.2

$0.80

Output Price per Million Tokens

GPT-3.5 Turbo 16k

$4.00

GLM 5.2

$2.50

💡 Cost Ratio: GLM 5.2 is 3.8x cheaper per input token than GPT-3.5 Turbo 16k.

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
79.4%vs89.5%+10.1% GLM 5.2
GPT-3.5 Turbo 16k
GLM 5.2 🏆
HumanEvalPython coding & logic synthesis
77.6%vs91.2%+13.6% GLM 5.2
GPT-3.5 Turbo 16k
GLM 5.2 🏆
MATHComplex mathematical problem solving
54.8%vs80.5%+25.7% GLM 5.2
GPT-3.5 Turbo 16k
GLM 5.2 🏆
GPQAGraduate-level expert reasoning
40.2%vs53.5%+13.3% GLM 5.2
GPT-3.5 Turbo 16k
GLM 5.2 🏆
HellaSwagCommonsense reasoning and inference
82.4%vs89.8%+7.4% GLM 5.2
GPT-3.5 Turbo 16k
GLM 5.2 🏆
MT-BenchMulti-turn conversation flow quality
8.5%vs9.3%+0.8% GLM 5.2
GPT-3.5 Turbo 16k
GLM 5.2 🏆

GPT-3.5 Turbo 16k Quirks & Gotchas

No developer gotchas reported.

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

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