LLM Reference

GLM-4V 9B

Released
2024-06-05
Last refreshed
2026-05-19
Status
Researched 16d ago
MultimodalLong contextVision

GLM-4V 9B is worth evaluating for long context and vision when its provider route and context window match the workload.

Use it for

  • Teams evaluating long context and vision
  • Workloads that can use a 131k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Strict JSON or tool-calling flows
Specifications
Family
GLM-4
Released
2024-06-05
Context
131k
Parameters
9B
Architecture
Decoder Only
Specialization
general
Training
finetuned
Created by

Leading China's LLM innovation surge

Beijing, China
Founded 2018
Website
Pricing
Output / 1M
$0.250
Input / 1M
$0.050

Cheapest of 1 route · Replicate API

About

GLM-4V 9B is Tsinghua Knowledge Engineering Group (THUDM)'s GLM-4 model with multimodal text and image input. It offers a 128K-token context window and scores 48.3 on MMMU.

GLM-4V 9B is a model in the GLM-4 family. The structured metadata tracks a 131k-token context window and multimodal input. This page tracks provider routes through Replicate API, with the cheapest tracked route listed at $0.05 input and $0.25 output per 1M tokens. Headline tracked benchmarks include Massive Multi-discipline Multimodal Understanding 48.3.

Top use-case fit

Long context

Included by capability and metadata signals in the decision map.

Vision

Q/$ A

1 relevant benchmark in the decision map.

Provider price ladder

Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Replicate API$0.050$0.250
Serverless

Capabilities

Multimodal

Benchmark peer barsfor Vision

Benchmark scores(1)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
Massive Multi-discipline Multimodal Understanding48.3https://mmmu-benchmark.github.io/

Migration checks

No linked migration route is available for this model yet.

Rankings & picks(7)

Comparison and alternatives

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