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GLM 5.1 vs GLM 4.7 Flash

Detailed technical comparison between GLM 5.1 (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.

⚡ Executive Summary & Verdict

Comparison Snapshot

GLM 5.1: 6 WinsvsGLM 4.7 Flash: 0 Wins
Context Leader

GLM 5.1

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 5.1

GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on...

View GLM 5.1 Full Specs →
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 →

Technical Specifications

🏆 = Superior Spec
SpecificationGLM 5.1GLM 4.7 Flash
ProviderZhipu AIZhipu AI
Context Window204,800 tokens🏆202,752 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-072026-01-19

API Pricing Comparison

Input Price per Million Tokens

GLM 5.1

$0.97

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

GLM 5.1

$3.04

GLM 4.7 Flash

$0.40

💡 Cost Ratio: GLM 4.7 Flash is 16.1x cheaper per input token than GLM 5.1.

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
88.0%vs77.2%+10.8% GLM 5.1
GLM 5.1 🏆
GLM 4.7 Flash
HumanEvalPython coding & logic synthesis
89.5%vs78.5%+11.0% GLM 5.1
GLM 5.1 🏆
GLM 4.7 Flash
MATHComplex mathematical problem solving
77.0%vs40.0%+37.0% GLM 5.1
GLM 5.1 🏆
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
51.0%vs31.0%+20.0% GLM 5.1
GLM 5.1 🏆
GLM 4.7 Flash
HellaSwagCommonsense reasoning and inference
88.5%vs80.0%+8.5% GLM 5.1
GLM 5.1 🏆
GLM 4.7 Flash
MT-BenchMulti-turn conversation flow quality
9.2%vs8.1%+1.1% GLM 5.1
GLM 5.1 🏆
GLM 4.7 Flash

GLM 5.1 Quirks & Gotchas

No developer gotchas reported.

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

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