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GLM 4.5 Air vs DeepSeek V3.1

Detailed technical comparison between GLM 4.5 Air (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.

โšก Executive Summary & Verdict

Comparison Snapshot

GLM 4.5 Air: 6 WinsvsDeepSeek V3.1: 0 Wins
Context Leader

DeepSeek V3.1

163,840 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GLM 4.5 Air

$0.13 / MTok
Zhipu AIactive

GLM 4.5 Air

GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter...

View GLM 4.5 Air Full Specs โ†’
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 โ†’

Technical Specifications

๐Ÿ† = Superior Spec
SpecificationGLM 4.5 AirDeepSeek V3.1
ProviderZhipu AIDeepSeek
Context Window131,072 tokens163,840 tokens๐Ÿ†
Agent SuitabilityNot yet benchmarkedNot yet benchmarked
Time to First Token (TTFT)No public TTFT dataNo public TTFT data
Deployment Modelmanaged apiself hostable
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2025-07-252025-08-21

API Pricing Comparison

Input Price per Million Tokens

GLM 4.5 Air

$0.13

DeepSeek V3.1

$0.25

Output Price per Million Tokens

GLM 4.5 Air

$0.85

DeepSeek V3.1

$0.95

๐Ÿ’ก Cost Ratio: GLM 4.5 Air is 1.9x cheaper per input token than DeepSeek V3.1.

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.

Benchmark Performance Metrics

Standardized Scores (0โ€“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
80.4%vs80.0%+0.4% GLM 4.5 Air
GLM 4.5 Air ๐Ÿ†
DeepSeek V3.1
HumanEvalPython coding & logic synthesis
78.6%vs78.2%+0.4% GLM 4.5 Air
GLM 4.5 Air ๐Ÿ†
DeepSeek V3.1
MATHComplex mathematical problem solving
55.8%vs55.4%+0.4% GLM 4.5 Air
GLM 4.5 Air ๐Ÿ†
DeepSeek V3.1
GPQAGraduate-level expert reasoning
41.2%vs40.8%+0.4% GLM 4.5 Air
GLM 4.5 Air ๐Ÿ†
DeepSeek V3.1
HellaSwagCommonsense reasoning and inference
83.4%vs83.0%+0.4% GLM 4.5 Air
GLM 4.5 Air ๐Ÿ†
DeepSeek V3.1
MT-BenchMulti-turn conversation flow quality
8.6%vs8.6%+0.0% GLM 4.5 Air
GLM 4.5 Air ๐Ÿ†
DeepSeek V3.1

GLM 4.5 Air Quirks & Gotchas

No developer gotchas reported.

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

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