GLM 4.6
Z.ai's open-weight flagship MoE model for coding, reasoning, and agentic tasks.
Get API key- Provider
- Z.ai (Zhipu AI)
- Price
- $0.43 in · $1.75 out / 1M
- Context window
- 198K tokens
- Released
- September 30, 2025
- License
- MIT
What is GLM 4.6?
GLM 4.6 is Z.ai's open-weight flagship language model, released September 2025. A 357B-parameter Mixture-of-Experts text model with strong coding, reasoning, and agentic capabilities, it ships with an MIT license, supports tool use and web search, and competes with leading proprietary models on math and code benchmarks.
Use it privately on Venice
On Venice, GLM 4.6 runs privately with zero retention — your prompts are not stored or used for training. You get the full open-weight model with tool use, reasoning, and web search capabilities, plus structured JSON output, all without Big-Tech surveillance. Because the weights are open and inference is permissionless, you maintain sovereignty over your data while accessing a top-tier coding and agentic model.
What can it do?
- •Open-weight MIT-licensed model with a 357B-parameter Mixture-of-Experts architecture, enabling self-hosting, auditing, and transparency outside Venice.
- •Strong coding and reasoning performance with native support for function calling, extended reasoning, web search, and structured JSON schema output.
- •Competitive with leading proprietary models on public math and coding leaderboards, including near-parity with Claude Sonnet 4 on several benchmarks per Z.ai's own evaluations.
- •Cost-efficient per-token pricing and high inference speed relative to closed rivals of similar capability.
- •Fully open weights under the MIT license, so you can deploy or fine-tune without vendor lock-in.
- •Not uncensored on Venice — it follows standard safety guidelines, so users seeking fully unrestricted outputs should self-host the open weights.
- •Served at fp4 quantization on Venice, which trades a small amount of precision for efficiency compared to full-precision inference.
- •Lags behind the very top closed coding models such as Claude Sonnet 4.5 and Claude Opus 4.6 on select complex coding tasks, per Z.ai's own blog.
- •No end-to-end encryption or TEE inference on Venice; privacy relies on Venice's zero-retention policy rather than cryptographic guarantees.
GLM 4.6 capabilities
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
How to use it via API
Venice exposes an OpenAI-compatible API. Swap your base URL and call zai-org-glm-4.6.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "zai-org-glm-4.6",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Specifications
Pricing
Billed per token on Venice: $0.43 per 1M input tokens and $1.75 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
GLM 4.6 vs alternatives
| Model | Context | Open weights | Price (Venice) | Strongest at |
|---|---|---|---|---|
| GLM 4.6 | 198K tokens | Yes | $0.43 in · $1.75 out / 1M | Coding & agentic tasks |
| GLM 5.1 | 200K tokens | Yes | $1.10 in · $4.15 out / 1M | Next-gen GLM successor |
| DeepSeek V3.2 | 160K tokens | Yes | $0.33 in · $0.48 out / 1M | Efficient open coding |
| Claude Sonnet 4.6 | 1M tokens | No | $3.60 in · $18 out / 1M | Proprietary reasoning |
Top open-weight balance of coding skill, reasoning, and price on Venice.
What is it good for?
- •Agentic coding with function-calling tools such as Claude Code, Cline, Roo Code, and Kilo Code.
- •Long-context document analysis and multi-turn agentic workflows within its 198K-token window.
- •Automated reasoning and search-based research tasks using the built-in web search capability.
- •Structured data extraction and API workflow automation via JSON schema output.
- •Role-playing and creative writing where natural style alignment and human-like readability matter.
Prompting tips
- •Enable reasoning and tool use for complex coding or math problems to unlock the model's advanced inference mode.
- •Use structured JSON schema output when building agents that need reliable, parseable responses.
- •For long-context tasks, place key instructions near the start of the prompt to improve recall across the full window.
- •Leverage web search to ground responses in current information beyond the model's training cutoff.
Frequently asked questions
GLM 4.6 is Z.ai's open-weight flagship language model released in September 2025. It is a 357B-parameter Mixture-of-Experts text model with strong coding, reasoning, and agentic capabilities, supporting tool use, web search, and structured JSON output under an MIT license.
On Venice, GLM 4.6 costs $0.43 per 1M input tokens and $1.75 per 1M output tokens, with cached input at $0.08 per 1M tokens. You pay only for what you use with no subscription required.
Yes. GLM 4.6 is released under the MIT license with open weights available on Hugging Face, so you can inspect, self-host, or fine-tune it outside of Venice.
Venice offers free trial credits for new users, so you can test GLM 4.6 without a credit card. Beyond the trial, usage is billed per token at the listed rates.
Yes. On Venice, GLM 4.6 supports function calling, reasoning, web search, and structured JSON schema output, making it well suited for agentic workflows and automated pipelines.
Claude Sonnet 4.6 leads on raw reasoning and offers a 1M-token context, but GLM 4.6 is far cheaper, fully open-weight, and nearly matches it on many coding benchmarks. Choose Sonnet for maximum context; choose GLM 4.6 for sovereignty and cost efficiency.
No. GLM 4.6 is not flagged as uncensored on Venice, so it follows standard safety guidelines. For fully uncensored outputs, you would need to self-host the open weights with custom moderation removed.
GLM 4.6 runs under Venice's private tier with zero retention — your prompts are not stored, profiled, or used for training. However, it does not currently run in a TEE or with end-to-end encryption.
Related models
Run GLM 4.6 privately.
No prompt logging. No data used for training. Free to start — no credit card.
