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Claude Opus 4.7 vs GLM 4.7 Flash

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude Opus 4.7 and GLM 4.7 Flash.

Anthropic

Claude Opus 4.7

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

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Zhipu AI

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,...

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Technical Specifications

SpecificationClaude Opus 4.7GLM 4.7 Flash
ProviderAnthropicZhipu AI
Context Window1,000,000 tokens202,752 tokens
Agent Suitability96/100N/A
Time to First Token (TTFT)480 msN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-162026-01-19

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.7

$5.00

GLM 4.7 Flash

$0.06

Output Price per Million Tokens

Claude Opus 4.7

$25.00

GLM 4.7 Flash

$0.40

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9410.0%vs7720.0%
Claude Opus 4.7
GLM 4.7 Flash
HumanEvalPython coding & logic synthesis
9610.0%vs7850.0%
Claude Opus 4.7
GLM 4.7 Flash
MATHComplex mathematical problem solving
9150.0%vs4000.0%
Claude Opus 4.7
GLM 4.7 Flash
GPQAGraduate-level expert reasoning
8420.0%vs3100.0%
Claude Opus 4.7
GLM 4.7 Flash
HellaSwagCommonsense reasoning and inference
9880.0%vs8000.0%
Claude Opus 4.7
GLM 4.7 Flash
MT-BenchMulti-turn conversation flow quality
975.0%vs810.0%
Claude Opus 4.7
GLM 4.7 Flash

Claude Opus 4.7 Quirks & Gotchas

  • โ–ธTop-tier agentic coding model โ€” excels at autonomous software engineering
  • โ–ธRequires explicit tool_choice parameter for parallel function calling to work reliably

GLM 4.7 Flash Quirks & Gotchas

No developer gotchas reported.