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GLM 4.7 Flash vs DeepSeek V3.1

Detailed technical comparison between GLM 4.7 Flash (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 4.7 Flash: 1 WinvsDeepSeek V3.1: 5 Wins
Context Leader

GLM 4.7 Flash

202,752 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GLM 4.7 Flash

$0.06 / MTok
Zhipu AIactive

GLM 4.7 Flash

As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...

View GLM 4.7 Flash 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 4.7 FlashDeepSeek V3.1
ProviderZhipu AIDeepSeek
Context Window202,752 tokens🏆163,840 tokens
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 Date2026-01-192025-08-21

API Pricing Comparison

Input Price per Million Tokens

GLM 4.7 Flash

$0.06

DeepSeek V3.1

$0.25

Output Price per Million Tokens

GLM 4.7 Flash

$0.40

DeepSeek V3.1

$0.95

💡 Cost Ratio: GLM 4.7 Flash is 4.2x cheaper per input token than DeepSeek V3.1.

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
77.2%vs80.0%+2.8% DeepSeek V3.1
GLM 4.7 Flash
DeepSeek V3.1 🏆
HumanEvalPython coding & logic synthesis
78.5%vs78.2%+0.3% GLM 4.7 Flash
GLM 4.7 Flash 🏆
DeepSeek V3.1
MATHComplex mathematical problem solving
40.0%vs55.4%+15.4% DeepSeek V3.1
GLM 4.7 Flash
DeepSeek V3.1 🏆
GPQAGraduate-level expert reasoning
31.0%vs40.8%+9.8% DeepSeek V3.1
GLM 4.7 Flash
DeepSeek V3.1 🏆
HellaSwagCommonsense reasoning and inference
80.0%vs83.0%+3.0% DeepSeek V3.1
GLM 4.7 Flash
DeepSeek V3.1 🏆
MT-BenchMulti-turn conversation flow quality
8.1%vs8.6%+0.5% DeepSeek V3.1
GLM 4.7 Flash
DeepSeek V3.1 🏆

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

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