GLM-4.7
ExterneGLM-4.7 is a powerful open-weight language model from Z.ai, optimized for advanced coding, agentic workflows, and creative UI generation. It sets new benchmarks with 73.8% on SWE-bench Verified, 87.4% on τ²-Bench for tool use, and innovative thinking modes like Interleaved, Preserved, and Turn-level for superior reasoning. Ideal for developers building coding agents, multilingual teams, and budget-conscious users seeking high-accuracy performance with local deployment flexibility.
Description
GLM-4.7 is a powerful open-weight language model from Z.ai, optimized for advanced coding, agentic workflows, and creative UI generation. It sets new benchmarks with 73.8% on SWE-bench Verified, 87.4% on τ²-Bench for tool use, and innovative thinking modes like Interleaved, Preserved, and Turn-level for superior reasoning. Ideal for developers building coding agents, multilingual teams, and budget-conscious users seeking high-accuracy performance with local deployment flexibility.
Capacités clés
- Exceptional coding performance (SWE-bench Verified 73.8%, Terminal Bench 41%)
- Strong tool use and agentic reasoning (τ²-Bench 87.4%)
- Advanced thinking modes (Interleaved, Preserved, Turn-level)
- Long context length up to 200K tokens
- Multilingual coding support
Cas d'usage principaux
- 1.Building coding agents and terminals
- 2.Generating UI, webpages, and slides
- 3.Creating interactive WebGL/3D content
- 4.Multilingual software engineering
- 5.Complex multi-turn agent workflows
- 6.Visual content like posters and portfolios
GLM-4.7 est-il pour vous ?
Idéal pour
- Developers building coding agents
- Multilingual coding teams
- Budget-conscious users with local hosting
- Teams needing stable multi-turn reasoning
Pas idéal pour
- Low-latency response applications
- High-volume repetitive tasks
- Speed or cost-per-token sensitive workloads
Fonctions phares
- Interleaved Thinking for better instruction following
- Preserved Thinking for multi-turn stability
- Turn-level Thinking for latency trade-offs
- Open weights on HuggingFace for local inference
- API access via Z.ai and OpenRouter
- Supports vLLM, SGLang frameworks
Tarifs
Pro
Free
Lite
Max
Highlights Feedback
Points Forts
- Top-tier coding benchmark results
- Reliable tool calls and multi-step reasoning
- Cost-effective open-source deployment
- Improved UI generation and creative writing
- Gains in multilingual and terminal tasks
Plaintes Communes
- Flash variant weaker on complex prompts
- Higher latency and costs for full model
- Inconsistencies in long-horizon tasks
- Bugs in reasoning token handling
- Verbose output increases token usage
- Occasional tool-calling issues