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GLM 4.5V vs DeepSeek V3.1

Detailed technical comparison between GLM 4.5V (Zhipu AI) and DeepSeek V3.1 (DeepSeek). 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 4.5V: 0 WinsvsDeepSeek V3.1: 6 Wins
Context Leader

DeepSeek V3.1

163,840 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

DeepSeek V3.1

$0.25 / MTok
Zhipu AIactive

GLM 4.5V

GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...

View GLM 4.5V Full Specs →
DeepSeekactive

DeepSeek V3.1

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

View DeepSeek V3.1 Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationGLM 4.5VDeepSeek V3.1
ProviderZhipu AIDeepSeek
Context Window65,536 tokens163,840 tokens🏆
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-08-112025-08-21

API Pricing Comparison

Input Price per Million Tokens

GLM 4.5V

$0.60

DeepSeek V3.1

$0.25

Output Price per Million Tokens

GLM 4.5V

$1.80

DeepSeek V3.1

$0.95

💡 Cost Ratio: DeepSeek V3.1 is 2.4x cheaper per input token than GLM 4.5V.

Want to test both models live?

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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
79.4%vs80.0%+0.6% DeepSeek V3.1
GLM 4.5V
DeepSeek V3.1 🏆
HumanEvalPython coding & logic synthesis
77.6%vs78.2%+0.6% DeepSeek V3.1
GLM 4.5V
DeepSeek V3.1 🏆
MATHComplex mathematical problem solving
54.8%vs55.4%+0.6% DeepSeek V3.1
GLM 4.5V
DeepSeek V3.1 🏆
GPQAGraduate-level expert reasoning
40.2%vs40.8%+0.6% DeepSeek V3.1
GLM 4.5V
DeepSeek V3.1 🏆
HellaSwagCommonsense reasoning and inference
82.4%vs83.0%+0.6% DeepSeek V3.1
GLM 4.5V
DeepSeek V3.1 🏆
MT-BenchMulti-turn conversation flow quality
8.5%vs8.6%+0.1% DeepSeek V3.1
GLM 4.5V
DeepSeek V3.1 🏆

GLM 4.5V Quirks & Gotchas

No developer gotchas reported.

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

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