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GLM 5 vs GLM 4.7 Flash

Detailed technical comparison between GLM 5 (Zhipu AI) and GLM 4.7 Flash (Zhipu AI). 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

GLM 5: 6 WinsvsGLM 4.7 Flash: 0 Wins
Context Leader

GLM 5

204,800 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GLM 4.7 Flash

$0.06 / MTok
Zhipu AIactive

GLM 5

GLM-5 is Z.aiโ€™s flagship open-source foundation model engineered for complex systems design and long-horizon agent workflows. Built for expert developers, it delivers production-grade performance on large-scale programming tasks, rivaling leading...

View GLM 5 Full Specs โ†’
Zhipu AIactive

GLM 4.7 Flash

As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...

View GLM 4.7 Flash Full Specs โ†’

Technical Specifications

๐Ÿ† = Superior Spec
SpecificationGLM 5GLM 4.7 Flash
ProviderZhipu AIZhipu AI
Context Window204,800 tokens๐Ÿ†202,752 tokens
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 Date2026-02-112026-01-19

API Pricing Comparison

Input Price per Million Tokens

GLM 5

$0.95

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

GLM 5

$2.55

GLM 4.7 Flash

$0.40

๐Ÿ’ก Cost Ratio: GLM 4.7 Flash is 15.8x cheaper per input token than GLM 5.

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
86.5%vs77.2%+9.3% GLM 5
GLM 5 ๐Ÿ†
GLM 4.7 Flash
HumanEvalPython coding & logic synthesis
87.0%vs78.5%+8.5% GLM 5
GLM 5 ๐Ÿ†
GLM 4.7 Flash
MATHComplex mathematical problem solving
74.0%vs40.0%+34.0% GLM 5
GLM 5 ๐Ÿ†
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
48.0%vs31.0%+17.0% GLM 5
GLM 5 ๐Ÿ†
GLM 4.7 Flash
HellaSwagCommonsense reasoning and inference
87.0%vs80.0%+7.0% GLM 5
GLM 5 ๐Ÿ†
GLM 4.7 Flash
MT-BenchMulti-turn conversation flow quality
9.1%vs8.1%+1.0% GLM 5
GLM 5 ๐Ÿ†
GLM 4.7 Flash

GLM 5 Quirks & Gotchas

No developer gotchas reported.

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

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