AI Models · Open-Source vs Paid

GLM 5.2 Open vs Gemini 3.1 Pro Preview Paid

GLM 5.2 vs Gemini 3.1 Pro Preview compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.

Prices & specs refreshed from live data · OpenSourceAI.tech

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

Choose GLM 5.2 if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Gemini 3.1 Pro Preview if you want frontier capability through a managed API with zero infrastructure to run.

GLM 5.2 vs Gemini 3.1 Pro Preview specs

SpecGLM 5.2Gemini 3.1 Pro Preview
MakerZ.AIGoogle
TypeOpen-weightProprietary
Context window1M tokens1M tokens
Input price$0.78/M · free self-host$2/M
Output price$2.44/M · free self-host$12/M
Vision / multimodalNoYes
Tool / function callingYesYes
Self-hostableYesNo (API only)
LicenseMITProprietary

Feature comparison

CapabilityGLM 5.2Gemini 3.1 Pro Preview
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: GLM 5.2 vs Gemini 3.1 Pro Preview

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

GLM 5.2 delivers 2.3× more intelligence per dollar.
GLM 5.2
Gemini 3.1 Pro Preview
Intelligence index
51.1
46.5
Coding index
68.8
68.8
GPQA
89.5%
94.1%
Humanity's Last Exam
40.1%
44.7%
Long Context Reasoning
71.3%
72.7%
SciCode
50.5%
58.9%
IFBench
73.3%
77.1%
τ²-Bench
99.1%
95.6%
τ-Bench Banking
26.8%
16.5%
Terminal-Bench
77.9%
73.8%
Terminal-Bench Hard
50.8%
53.8%
Speed
198.1 tok/s
137.1 tok/s
Latency
0.85s
23.58s
Intelligence per $
23.8
10.3

Benchmark data by Artificial Analysis.

How GLM 5.2 and Gemini 3.1 Pro Preview score

🏆 Best value & openness: GLM 5.2 (4.6 vs 3.2 / 5)
CriterionGLM 5.2Gemini 3.1 Pro Preview
Cost-efficiency4.53.5
Context window5.05.0
Openness5.01.5
Self-hosting5.01.0
Multimodality3.55.0

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

GLM 5.2 Open

Z.AI · Open-weight

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,...

Gemini 3.1 Pro Preview Paid

Google · Proprietary

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation.

Other models in these families

These variants are tracked but not compared here — one page per family keeps the comparison readable.

Other variants tracked
GLM 5GLM 5.1GLM 4.7GLM 4.7 FlashGLM 4.6GLM 4.5 AirGLM 5 TurboGLM 5V TurboGLM 4.5GLM 4.6VGLM 4.5V
Other variants tracked
Gemini 2.5 Pro

Frequently asked questions

Is GLM 5.2 as good as Gemini 3.1 Pro Preview?

GLM 5.2 is open-weight and competitive on many tasks, but Gemini 3.1 Pro Preview may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.

Can I run GLM 5.2 locally?

Yes. GLM 5.2 has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Gemini 3.1 Pro Preview is API-only and cannot be self-hosted.

How much cheaper is GLM 5.2?

GLM 5.2 costs $2.44/M output vs $12/M for Gemini 3.1 Pro Preview — roughly 5x cheaper via API, and free if you self-host.

GLM 5.2 vs Gemini 3.1 Pro Preview — which should I pick in 2026?

Choose GLM 5.2 if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Gemini 3.1 Pro Preview if you want frontier capability through a managed API with zero infrastructure to run.

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