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Zhipu AI · GLM
No. 33

GLM-4.7

Efficient open coding workhorse for everyday dev tasks.

OpenOpen weightsText
Field notes
Context window
200Ktokens
Max output
131Ktokens
Input price
$0.60/ 1M tokens
Output price
$2.20/ 1M tokens
Cached input
$0.11/ 1M tokens
Modalities
Text
Knowledge cutoff
Oct 2025
Released
Dec 2025
Parameters
355B
License
MIT
Approx. speed
Overview

What this model is

GLM-4.7 is Zhipu's cheaper, faster open-weight coding model, widely used as the value tier of the GLM Coding Plan and as a Claude Code-compatible backend. It handles routine multi-file coding, tool use, and reasoning capably at a fraction of flagship cost, but steps down from GLM-5.2 on the hardest long-horizon tasks. MIT-licensed and self-hostable.

Strengths

  • Very low cost for capable coding
  • Faster and lighter than GLM-5.2
  • ~200K context for sizable repos
  • MIT open weights, self-hostable

Trade-offs

  • Below the flagship on complex multi-file work
  • Text-only, no vision
  • Agentic reliability well below the frontier
  • Superseded by GLM-5.2 on hard tasks

Best for

  • Budget coding assistants
  • Routine refactors and bug fixes
  • High-volume dev automation
  • Self-hosted coding backends

Not ideal for

  • Hardest long-horizon agentic coding
  • Workloads needing 1M-token context
Capabilities

Capability profile

Normalized 0–100 scores, comparable across the whole catalog.

Reasoning74Coding70Math80Writing76Knowledge78Speed80Agentic66Vision10Multilingual80Long Context74
Reasoning
74
Coding
70
Math
80
Writing
76
Knowledge
78
Speed
80
Agentic
66
Vision
10
Multilingual
80
Long Context
74
Benchmarks

How it scores

Public benchmark results, with independent third-party results where available. Bars normalize percentages to 100 and Elo ratings to a 1500 ceiling.

BenchmarkResult
SWE-bench Verifiedindependent
CodingSWE-bench
73.8%
AIME 2025
MathVendor-reported
95.7%
GPQA Diamondindependent
ReasoningIndependent aggregators
85.7%
LiveCodeBenchindependent
CodingLiveCodeBench
84.9%
Alternatives

Comparable models

Models in a roughly similar class — worth weighing against this one.